Cure Model Regression
cureit.RdCure Model Regression
Usage
# S3 method for formula
cureit(
surv_formula,
cure_formula,
data,
conf.level = 0.95,
nboot = 100,
eps = 1e-07,
...
)
cureit(object, ...)
# S3 method for default
cureit(object, ...)Arguments
- surv_formula
formula with
Surv()on LHS and covariates on RHS.- cure_formula
formula with covariates for cure fraction on RHS
- data
data frame
- conf.level
confidence level. Default is 0.95.
- nboot
number of bootstrap samples used for inference.
- eps
convergence criterion for the EM algorithm.
- ...
passed to methods
- object
input object
See also
Other cureit() functions:
Brier_inference_bootstrap(),
broom_methods_cureit,
nomogram(),
predict.cureit()
Examples
cureit(surv_formula = Surv(ttdeath, death) ~ age + grade,
cure_formula = ~ age + grade, data = trial)
#> 0 were not able to fit
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002616112 0.569504769 0.345883977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.575003030 0.009813492 0.108542405
#> grade_iii, Cure model
#> 0.823899189
#>
#> $surv_formula
#> Surv(ttdeath, death) ~ age + grade
#> <environment: 0x560ddebb1c48>
#>
#> $cure_formula
#> ~age + grade
#> <environment: 0x560ddebb1c48>
#>
#> $data
#> # A tibble: 200 × 8
#> trt age marker stage grade response death ttdeath
#> <chr> <dbl> <dbl> <fct> <fct> <int> <dbl> <dbl>
#> 1 Drug A 23 0.16 T1 II 0 0 24
#> 2 Drug B 9 1.11 T2 I 1 0 24
#> 3 Drug A 31 0.277 T1 II 0 0 24
#> 4 Drug A NA 2.07 T3 III 1 1 17.6
#> 5 Drug A 51 2.77 T4 III 1 1 16.4
#> 6 Drug B 39 0.613 T4 I 0 1 15.6
#> 7 Drug A 37 0.354 T1 II 0 0 24
#> 8 Drug A 32 1.74 T1 I 0 1 18.4
#> 9 Drug A 31 0.144 T1 II 0 0 24
#> 10 Drug B 34 0.205 T3 I 0 1 10.5
#> # ℹ 190 more rows
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> $surv_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $cure_xlevels
#> $cure_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure mod… -0.575 0.508 -1.13 -1.57 0.420 0.258
#> 2 age, Cure model 0.00981 0.0102 0.958 -0.0103 0.0299 0.338
#> 3 grade_ii, Cure model 0.109 0.362 0.300 -0.600 0.817 0.764
#> 4 grade_iii, Cure model 0.824 0.324 2.54 0.188 1.46 0.0111
#>
#> $tidy$df_surv
#> # A tibble: 3 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00262 0.00967 -0.270 -0.0216 0.0163 0.787
#> 2 grade_ii, Survival mo… 0.570 0.285 2.00 0.0107 1.13 0.0458
#> 3 grade_iii, Survival m… 0.346 0.256 1.35 -0.155 0.847 0.176
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003 0.009813 0.108542 0.823899
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003030 0.009813492 0.108542405 0.823899189
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002616112 0.569504769 0.345883977
#>
#> $b_var
#> [1] 0.2579391941 0.0001050289 0.1308160194 0.1052314725
#>
#> $b_sd
#> [1] 0.50787714 0.01024836 0.36168497 0.32439401
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1321695 0.9575672 0.3001021 2.5398101
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.25756317 0.33828102 0.76409931 0.01109127
#>
#> $beta_var
#> [1] 9.359265e-05 8.127206e-02 6.536551e-02
#>
#> $beta_sd
#> [1] 0.00967433 0.28508256 0.25566679
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.2704179 1.9976837 1.3528702
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.78683877 0.04575097 0.17609710
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.000000000 0.000000000 0.000000000 0.604678067 0.658063410 0.000000000
#> [7] 0.417229340 0.000000000 0.879376354 0.000000000 0.000000000 0.744886187
#> [13] 0.787600867 0.142672058 0.944518547 0.000000000 0.693100768 0.000000000
#> [19] 0.000000000 0.000000000 0.000000000 0.540871173 0.006912639 0.976381134
#> [25] 0.640373656 0.000000000 0.000000000 0.684419417 0.522291631 0.000000000
#> [31] 0.278243702 0.000000000 0.000000000 0.000000000 0.246976530 0.821307758
#> [37] 0.000000000 0.666890646 0.466018936 0.456394953 0.829660071 0.854634203
#> [43] 0.000000000 0.531599829 0.000000000 0.000000000 0.000000000 0.846335953
#> [49] 0.446649365 0.887603756 0.000000000 0.000000000 0.368370905 0.837991986
#> [55] 0.736284601 0.368370905 0.762052697 0.904005497 0.000000000 0.130947018
#> [61] 0.000000000 0.000000000 0.178167087 0.000000000 0.298558895 0.093531067
#> [67] 0.960518552 0.000000000 0.000000000 0.000000000 0.000000000 0.387858887
#> [73] 0.968455884 0.020860827 0.613665875 0.000000000 0.753465281 0.000000000
#> [79] 0.000000000 0.000000000 0.586773524 0.036370054 0.000000000 0.427038837
#> [85] 0.267747949 0.984266892 0.106209363 0.895813391 0.000000000 0.000000000
#> [91] 0.727657186 0.397671772 0.000000000 0.246976530 0.631469660 0.920311545
#> [97] 0.000000000 0.000000000 0.000000000 0.348502061 0.550166021 0.862915985
#> [103] 0.436874482 0.000000000 0.494318881 0.513013956 0.000000000 0.118522726
#> [109] 0.000000000 0.503694197 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.779118376 0.649247645 0.000000000 0.992139734 0.308649170
#> [121] 0.080274841 0.568542449 0.000000000 0.000000000 0.718999352 0.475516896
#> [127] 0.000000000 0.201867710 0.000000000 0.000000000 0.224987874 0.796088245
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.912176411 0.000000000
#> [139] 0.000000000 0.000000000 0.952539418 0.318644852 0.000000000 0.000000000
#> [145] 0.236117909 0.804529313 0.770582430 0.000000000 0.701722215 0.328677697
#> [151] 0.871155498 0.000000000 0.000000000 0.000000000 0.000000000 0.065734870
#> [157] 0.000000000 0.338572747 0.675684959 0.050684149 0.154512416 0.358472658
#> [163] 0.559374570 0.000000000 0.000000000 0.000000000 0.189977968 0.000000000
#> [169] 0.812910823 0.000000000 0.407438340 0.710355937 0.577676416 0.000000000
#> [175] 0.936485829 0.484909262 0.000000000 0.000000000 0.928419678 0.622583868
#> [181] 0.288505592 0.000000000 0.586773524 0.000000000 0.166456957 0.000000000
#> [187] 0.213576414 0.000000000 0.000000000
#>
#> $Time
#> 1 2 3 5 6 7 8 9 10 11 12 13 14
#> 24.00 24.00 24.00 16.43 15.64 24.00 18.43 24.00 10.53 24.00 24.00 14.34 12.89
#> 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 22.68 8.71 24.00 15.21 24.00 24.00 24.00 24.00 16.92 23.89 6.32 15.77 24.00
#> 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 24.00 15.45 17.43 24.00 20.90 24.00 24.00 24.00 21.19 12.52 24.00 15.59 18.00
#> 41 42 43 44 45 46 47 48 49 51 52 53 54
#> 18.02 12.43 12.10 24.00 17.42 24.00 24.00 24.00 12.19 18.23 10.42 24.00 24.00
#> 55 56 57 58 60 61 62 63 64 65 66 67 68
#> 19.34 12.21 14.46 19.34 13.15 10.12 24.00 22.77 24.00 24.00 22.13 24.00 20.62
#> 69 70 71 72 74 75 76 77 78 79 80 81 82
#> 23.23 7.38 24.00 24.00 24.00 24.00 19.22 7.27 23.88 16.23 24.00 14.06 24.00
#> 83 84 85 86 87 88 90 91 92 93 94 95 96
#> 24.00 24.00 16.44 23.81 24.00 18.37 20.94 5.33 22.92 10.33 24.00 24.00 14.54
#> 97 98 99 100 101 102 103 104 105 106 107 108 109
#> 19.14 24.00 21.19 16.07 9.97 24.00 24.00 24.00 19.75 16.67 11.18 18.29 24.00
#> 110 111 112 113 116 117 118 119 120 121 122 123 125
#> 17.56 17.45 24.00 22.86 24.00 17.46 24.00 24.00 24.00 24.00 24.00 13.00 15.65
#> 126 127 128 129 130 131 132 133 134 135 136 137 138
#> 24.00 3.53 20.35 23.41 16.47 24.00 24.00 14.65 17.81 24.00 21.83 24.00 24.00
#> 139 140 141 142 143 144 145 146 147 148 149 150 151
#> 21.49 12.68 24.00 24.00 24.00 24.00 10.07 24.00 24.00 24.00 8.37 20.33 24.00
#> 152 153 154 155 156 157 158 159 160 161 162 163 164
#> 24.00 21.33 12.63 13.08 24.00 15.10 20.14 10.55 24.00 24.00 24.00 24.00 23.60
#> 165 166 167 168 169 170 171 172 173 174 175 176 177
#> 24.00 19.98 15.55 23.72 22.41 19.54 16.57 24.00 24.00 24.00 21.91 24.00 12.53
#> 178 179 180 181 182 183 184 185 186 187 188 190 191
#> 24.00 18.63 14.82 16.46 24.00 9.24 17.77 24.00 24.00 9.92 16.16 20.81 24.00
#> 192 193 194 196 197 198 200
#> 16.44 24.00 22.40 24.00 21.60 24.00 24.00
#>
#> $bootstrap_fit
#> $bootstrap_fit[[1]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0008696957 0.4636493422 0.4345520686
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.10494006 0.01057584 -1.01427546
#> grade_iii, Cure model
#> 0.51562935
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 91 5.33 1 61 0 1
#> 43 12.10 1 61 0 1
#> 6 15.64 1 39 0 0
#> 91.1 5.33 1 61 0 1
#> 145 10.07 1 65 1 0
#> 85 16.44 1 36 0 0
#> 197 21.60 1 69 1 0
#> 139 21.49 1 63 1 0
#> 153 21.33 1 55 1 0
#> 108 18.29 1 39 0 1
#> 6.1 15.64 1 39 0 0
#> 117 17.46 1 26 0 1
#> 125 15.65 1 67 1 0
#> 192 16.44 1 31 1 0
#> 168 23.72 1 70 0 0
#> 57 14.46 1 45 0 1
#> 6.2 15.64 1 39 0 0
#> 139.1 21.49 1 63 1 0
#> 101 9.97 1 10 0 1
#> 197.1 21.60 1 69 1 0
#> 114 13.68 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 23 16.92 1 61 0 0
#> 29 15.45 1 68 1 0
#> 124 9.73 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 69 23.23 1 25 0 1
#> 40 18.00 1 28 1 0
#> 114.1 13.68 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 63 22.77 1 31 1 0
#> 133.1 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 93 10.33 1 52 0 1
#> 70 7.38 1 30 1 0
#> 107 11.18 1 54 1 0
#> 188 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 124.1 9.73 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 90 20.94 1 50 0 1
#> 181 16.46 1 45 0 1
#> 133.2 14.65 1 57 0 0
#> 92 22.92 1 47 0 1
#> 129 23.41 1 53 1 0
#> 106 16.67 1 49 1 0
#> 188.1 16.16 1 46 0 1
#> 175 21.91 1 43 0 0
#> 39 15.59 1 37 0 1
#> 169 22.41 1 46 0 0
#> 90.1 20.94 1 50 0 1
#> 25 6.32 1 34 1 0
#> 91.2 5.33 1 61 0 1
#> 150 20.33 1 48 0 0
#> 179 18.63 1 42 0 0
#> 25.1 6.32 1 34 1 0
#> 30 17.43 1 78 0 0
#> 133.3 14.65 1 57 0 0
#> 56 12.21 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 43.1 12.10 1 61 0 1
#> 91.3 5.33 1 61 0 1
#> 123 13.00 1 44 1 0
#> 157 15.10 1 47 0 0
#> 129.1 23.41 1 53 1 0
#> 130 16.47 1 53 0 1
#> 14 12.89 1 21 0 0
#> 133.4 14.65 1 57 0 0
#> 8 18.43 1 32 0 0
#> 92.1 22.92 1 47 0 1
#> 171 16.57 1 41 0 1
#> 13 14.34 1 54 0 1
#> 107.1 11.18 1 54 1 0
#> 179.1 18.63 1 42 0 0
#> 97 19.14 1 65 0 1
#> 8.1 18.43 1 32 0 0
#> 69.1 23.23 1 25 0 1
#> 58 19.34 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 125.1 15.65 1 67 1 0
#> 68 20.62 1 44 0 0
#> 5 16.43 1 51 0 1
#> 24 23.89 1 38 0 0
#> 43.2 12.10 1 61 0 1
#> 43.3 12.10 1 61 0 1
#> 175.1 21.91 1 43 0 0
#> 97.1 19.14 1 65 0 1
#> 24.1 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 57.1 14.46 1 45 0 1
#> 179.2 18.63 1 42 0 0
#> 145.2 10.07 1 65 1 0
#> 183 9.24 1 67 1 0
#> 150.1 20.33 1 48 0 0
#> 181.1 16.46 1 45 0 1
#> 189.1 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 117.1 17.46 1 26 0 1
#> 171.1 16.57 1 41 0 1
#> 43.4 12.10 1 61 0 1
#> 99 21.19 1 38 0 1
#> 66 22.13 1 53 0 0
#> 168.1 23.72 1 70 0 0
#> 164 23.60 1 76 0 1
#> 199 19.81 1 NA 0 1
#> 23.1 16.92 1 61 0 0
#> 100 16.07 1 60 0 0
#> 92.2 22.92 1 47 0 1
#> 39.1 15.59 1 37 0 1
#> 26 15.77 1 49 0 1
#> 160 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 62 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 9 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 62.1 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 178 24.00 0 52 1 0
#> 182 24.00 0 35 0 0
#> 147.1 24.00 0 76 1 0
#> 182.1 24.00 0 35 0 0
#> 119 24.00 0 17 0 0
#> 75 24.00 0 21 1 0
#> 48 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 178.1 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 174.1 24.00 0 49 1 0
#> 9.1 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 198 24.00 0 66 0 1
#> 11.1 24.00 0 42 0 1
#> 28 24.00 0 67 1 0
#> 7 24.00 0 37 1 0
#> 74 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 9.2 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 141.1 24.00 0 44 1 0
#> 156.2 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 27.1 24.00 0 63 1 0
#> 138.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 74.1 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 178.2 24.00 0 52 1 0
#> 148 24.00 0 61 1 0
#> 102 24.00 0 49 0 0
#> 131 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 27.2 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 163 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 185.1 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 71.1 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 75.1 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 135.1 24.00 0 58 1 0
#> 144 24.00 0 28 0 1
#> 196 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 185.2 24.00 0 44 1 0
#> 27.3 24.00 0 63 1 0
#> 156.3 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 185.3 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 137 24.00 0 45 1 0
#> 103.2 24.00 0 56 1 0
#> 1.1 24.00 0 23 1 0
#> 44 24.00 0 56 0 0
#> 176.1 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 165 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 121.1 24.00 0 57 1 0
#> 176.2 24.00 0 43 0 1
#> 176.3 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.105 NA NA NA
#> 2 age, Cure model 0.0106 NA NA NA
#> 3 grade_ii, Cure model -1.01 NA NA NA
#> 4 grade_iii, Cure model 0.516 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000870 NA NA NA
#> 2 grade_ii, Survival model 0.464 NA NA NA
#> 3 grade_iii, Survival model 0.435 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.10494 0.01058 -1.01428 0.51563
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 245.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.10494006 0.01057584 -1.01427546 0.51562935
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0008696957 0.4636493422 0.4345520686
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.48744398 0.97340772 0.85393866 0.70947780 0.97340772 0.91106765
#> [7] 0.62872067 0.29027301 0.31228767 0.33329708 0.49682439 0.70947780
#> [13] 0.52443476 0.69380878 0.62872067 0.06569765 0.80901044 0.70947780
#> [19] 0.31228767 0.93199307 0.29027301 0.76369630 0.56001707 0.74827675
#> [25] 0.80137249 0.15622315 0.50610015 0.21885006 0.23122189 0.76369630
#> [31] 0.41281644 0.90392563 0.95288519 0.88962875 0.66170667 0.65351775
#> [37] 0.91106765 0.35401535 0.61203552 0.76369630 0.18373760 0.12561688
#> [43] 0.57760696 0.66170667 0.26704766 0.73282461 0.24318846 0.35401535
#> [49] 0.95978403 0.97340772 0.38346164 0.44120425 0.95978403 0.55113666
#> [55] 0.76369630 0.84647900 0.94595464 0.85393866 0.97340772 0.83155140
#> [61] 0.75598817 0.12561688 0.60349323 0.83901581 0.76369630 0.46884892
#> [67] 0.18373760 0.58638117 0.82404305 0.88962875 0.44120425 0.42253286
#> [73] 0.46884892 0.15622315 0.40295650 0.69380878 0.37356546 0.64525989
#> [79] 0.02496741 0.85393866 0.85393866 0.26704766 0.42253286 0.02496741
#> [85] 0.51527019 0.80901044 0.44120425 0.91106765 0.93899163 0.38346164
#> [91] 0.61203552 0.54224620 0.52443476 0.58638117 0.85393866 0.34374924
#> [97] 0.25513116 0.06569765 0.10585582 0.56001707 0.67774362 0.18373760
#> [103] 0.73282461 0.68580497 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 88 91 43 6 91.1 145 85 197 139 153 108 6.1 117
#> 18.37 5.33 12.10 15.64 5.33 10.07 16.44 21.60 21.49 21.33 18.29 15.64 17.46
#> 125 192 168 57 6.2 139.1 101 197.1 133 23 29 96 69
#> 15.65 16.44 23.72 14.46 15.64 21.49 9.97 21.60 14.65 16.92 15.45 14.54 23.23
#> 40 113 63 133.1 76 93 70 107 188 79 145.1 90 181
#> 18.00 22.86 22.77 14.65 19.22 10.33 7.38 11.18 16.16 16.23 10.07 20.94 16.46
#> 133.2 92 129 106 188.1 175 39 169 90.1 25 91.2 150 179
#> 14.65 22.92 23.41 16.67 16.16 21.91 15.59 22.41 20.94 6.32 5.33 20.33 18.63
#> 25.1 30 133.3 56 149 43.1 91.3 123 157 129.1 130 14 133.4
#> 6.32 17.43 14.65 12.21 8.37 12.10 5.33 13.00 15.10 23.41 16.47 12.89 14.65
#> 8 92.1 171 13 107.1 179.1 97 8.1 69.1 58 125.1 68 5
#> 18.43 22.92 16.57 14.34 11.18 18.63 19.14 18.43 23.23 19.34 15.65 20.62 16.43
#> 24 43.2 43.3 175.1 97.1 24.1 184 57.1 179.2 145.2 183 150.1 181.1
#> 23.89 12.10 12.10 21.91 19.14 23.89 17.77 14.46 18.63 10.07 9.24 20.33 16.46
#> 111 117.1 171.1 43.4 99 66 168.1 164 23.1 100 92.2 39.1 26
#> 17.45 17.46 16.57 12.10 21.19 22.13 23.72 23.60 16.92 16.07 22.92 15.59 15.77
#> 160 138 71 174 62 147 9 103 47 62.1 156 80 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 147.1 182.1 119 75 48 156.1 178.1 109 174.1 9.1 11 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 28 7 74 27 104 9.2 109.1 141 152 143 141.1 156.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 27.1 138.1 135 74.1 162 178.2 148 102 131 47.1 27.2 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 17 185 95 64 185.1 176 71.1 65 142 112 75.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 144 196 151 185.2 27.3 156.3 116 185.3 103.1 137 103.2 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 176.1 121 54 165 3 200 121.1 176.2 176.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[2]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008473307 0.801254229 0.157105465
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.06206577 0.01979643 0.03754818
#> grade_iii, Cure model
#> 0.80907097
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 128 20.35 1 35 0 1
#> 111 17.45 1 47 0 1
#> 111.1 17.45 1 47 0 1
#> 194 22.40 1 38 0 1
#> 79 16.23 1 54 1 0
#> 37 12.52 1 57 1 0
#> 139 21.49 1 63 1 0
#> 86 23.81 1 58 0 1
#> 171 16.57 1 41 0 1
#> 189 10.51 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 70 7.38 1 30 1 0
#> 50 10.02 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 86.1 23.81 1 58 0 1
#> 114 13.68 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 194.1 22.40 1 38 0 1
#> 15 22.68 1 48 0 0
#> 110 17.56 1 65 0 1
#> 110.1 17.56 1 65 0 1
#> 96 14.54 1 33 0 1
#> 157 15.10 1 47 0 0
#> 69 23.23 1 25 0 1
#> 158 20.14 1 74 1 0
#> 117 17.46 1 26 0 1
#> 175 21.91 1 43 0 0
#> 167 15.55 1 56 1 0
#> 111.2 17.45 1 47 0 1
#> 133 14.65 1 57 0 0
#> 59 10.16 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 86.2 23.81 1 58 0 1
#> 168 23.72 1 70 0 0
#> 192 16.44 1 31 1 0
#> 13.1 14.34 1 54 0 1
#> 168.1 23.72 1 70 0 0
#> 93 10.33 1 52 0 1
#> 32 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 26 15.77 1 49 0 1
#> 175.1 21.91 1 43 0 0
#> 88 18.37 1 47 0 0
#> 188 16.16 1 46 0 1
#> 77 7.27 1 67 0 1
#> 41 18.02 1 40 1 0
#> 61 10.12 1 36 0 1
#> 90 20.94 1 50 0 1
#> 25 6.32 1 34 1 0
#> 111.3 17.45 1 47 0 1
#> 181 16.46 1 45 0 1
#> 192.1 16.44 1 31 1 0
#> 190 20.81 1 42 1 0
#> 127 3.53 1 62 0 1
#> 29 15.45 1 68 1 0
#> 6 15.64 1 39 0 0
#> 145 10.07 1 65 1 0
#> 187 9.92 1 39 1 0
#> 13.2 14.34 1 54 0 1
#> 197 21.60 1 69 1 0
#> 154 12.63 1 20 1 0
#> 99 21.19 1 38 0 1
#> 169 22.41 1 46 0 0
#> 154.1 12.63 1 20 1 0
#> 36 21.19 1 48 0 1
#> 139.1 21.49 1 63 1 0
#> 195 11.76 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 90.1 20.94 1 50 0 1
#> 145.1 10.07 1 65 1 0
#> 157.1 15.10 1 47 0 0
#> 195.1 11.76 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 195.2 11.76 1 NA 1 0
#> 133.1 14.65 1 57 0 0
#> 30 17.43 1 78 0 0
#> 32.1 20.90 1 37 1 0
#> 36.1 21.19 1 48 0 1
#> 99.1 21.19 1 38 0 1
#> 171.1 16.57 1 41 0 1
#> 169.1 22.41 1 46 0 0
#> 168.2 23.72 1 70 0 0
#> 89 11.44 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 85 16.44 1 36 0 0
#> 68 20.62 1 44 0 0
#> 36.2 21.19 1 48 0 1
#> 68.1 20.62 1 44 0 0
#> 10 10.53 1 34 0 0
#> 107.1 11.18 1 54 1 0
#> 100 16.07 1 60 0 0
#> 36.3 21.19 1 48 0 1
#> 197.1 21.60 1 69 1 0
#> 140 12.68 1 59 1 0
#> 134 17.81 1 47 1 0
#> 157.2 15.10 1 47 0 0
#> 51 18.23 1 83 0 1
#> 133.2 14.65 1 57 0 0
#> 180 14.82 1 37 0 0
#> 100.1 16.07 1 60 0 0
#> 155 13.08 1 26 0 0
#> 57 14.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 86.3 23.81 1 58 0 1
#> 89.1 11.44 1 NA 0 0
#> 13.3 14.34 1 54 0 1
#> 32.2 20.90 1 37 1 0
#> 189.1 10.51 1 NA 1 0
#> 114.1 13.68 1 NA 0 0
#> 24.1 23.89 1 38 0 0
#> 160 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 109 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 82 24.00 0 34 0 0
#> 156 24.00 0 50 1 0
#> 112 24.00 0 61 0 0
#> 152 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 98.1 24.00 0 34 1 0
#> 67 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 165 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 27 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 19 24.00 0 57 0 1
#> 176 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 64 24.00 0 43 0 0
#> 47 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 98.2 24.00 0 34 1 0
#> 151.1 24.00 0 42 0 0
#> 48 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 122 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 3 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 165.1 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 160.1 24.00 0 31 1 0
#> 156.2 24.00 0 50 1 0
#> 138.1 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 20 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 122.1 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 46.1 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 147 24.00 0 76 1 0
#> 162 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 20.1 24.00 0 46 1 0
#> 53 24.00 0 32 0 1
#> 182 24.00 0 35 0 0
#> 116.1 24.00 0 58 0 1
#> 119.2 24.00 0 17 0 0
#> 74 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 27.1 24.00 0 63 1 0
#> 75.1 24.00 0 21 1 0
#> 35 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 53.1 24.00 0 32 0 1
#> 163 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 143.1 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 161 24.00 0 45 0 0
#> 53.2 24.00 0 32 0 1
#> 148 24.00 0 61 1 0
#> 143.2 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 53.3 24.00 0 32 0 1
#> 138.2 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 138.3 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 131 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 74.2 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0198 NA NA NA
#> 3 grade_ii, Cure model 0.0375 NA NA NA
#> 4 grade_iii, Cure model 0.809 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00847 NA NA NA
#> 2 grade_ii, Survival model 0.801 NA NA NA
#> 3 grade_iii, Survival model 0.157 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06207 0.01980 0.03755 0.80907
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.9
#> Residual Deviance: 250.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06206577 0.01979643 0.03754818 0.80907097
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008473307 0.801254229 0.157105465
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.757281578 0.320415263 0.453952434 0.453952434 0.099335251 0.567438433
#> [7] 0.854361821 0.162521311 0.014415405 0.505013512 0.854361821 0.958786512
#> [13] 0.875335149 0.014415405 0.003627096 0.099335251 0.069605829 0.423382749
#> [19] 0.423382749 0.735591657 0.661726426 0.060236618 0.350876082 0.443673671
#> [25] 0.119891469 0.630235045 0.453952434 0.703633623 0.403037858 0.014415405
#> [31] 0.036444970 0.536739666 0.757281578 0.036444970 0.906580477 0.261502510
#> [37] 0.361140779 0.609043242 0.119891469 0.371523097 0.577783713 0.969090231
#> [43] 0.392602533 0.917086522 0.240136382 0.979430976 0.453952434 0.526063753
#> [49] 0.536739666 0.290691989 0.989699027 0.640787721 0.619613647 0.927609144
#> [55] 0.948401530 0.757281578 0.141590466 0.833193791 0.182661414 0.079417780
#> [61] 0.833193791 0.182661414 0.162521311 0.800428190 0.240136382 0.927609144
#> [67] 0.661726426 0.703633623 0.494453516 0.261502510 0.182661414 0.182661414
#> [73] 0.505013512 0.079417780 0.036444970 0.651296717 0.536739666 0.300574835
#> [79] 0.182661414 0.300574835 0.896104403 0.875335149 0.588167591 0.182661414
#> [85] 0.141590466 0.822296226 0.413272428 0.661726426 0.382001621 0.703633623
#> [91] 0.693003369 0.588167591 0.811347639 0.746420793 0.330535452 0.330535452
#> [97] 0.014415405 0.757281578 0.261502510 0.003627096 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 13 128 111 111.1 194 79 37 139 86 171 37.1 70 107
#> 14.34 20.35 17.45 17.45 22.40 16.23 12.52 21.49 23.81 16.57 12.52 7.38 11.18
#> 86.1 24 194.1 15 110 110.1 96 157 69 158 117 175 167
#> 23.81 23.89 22.40 22.68 17.56 17.56 14.54 15.10 23.23 20.14 17.46 21.91 15.55
#> 111.2 133 40 86.2 168 192 13.1 168.1 93 32 105 26 175.1
#> 17.45 14.65 18.00 23.81 23.72 16.44 14.34 23.72 10.33 20.90 19.75 15.77 21.91
#> 88 188 77 41 61 90 25 111.3 181 192.1 190 127 29
#> 18.37 16.16 7.27 18.02 10.12 20.94 6.32 17.45 16.46 16.44 20.81 3.53 15.45
#> 6 145 187 13.2 197 154 99 169 154.1 36 139.1 60 90.1
#> 15.64 10.07 9.92 14.34 21.60 12.63 21.19 22.41 12.63 21.19 21.49 13.15 20.94
#> 145.1 157.1 133.1 30 32.1 36.1 99.1 171.1 169.1 168.2 18 85 68
#> 10.07 15.10 14.65 17.43 20.90 21.19 21.19 16.57 22.41 23.72 15.21 16.44 20.62
#> 36.2 68.1 10 107.1 100 36.3 197.1 140 134 157.2 51 133.2 180
#> 21.19 20.62 10.53 11.18 16.07 21.19 21.60 12.68 17.81 15.10 18.23 14.65 14.82
#> 100.1 155 57 150 150.1 86.3 13.3 32.2 24.1 160 38 98 109
#> 16.07 13.08 14.46 20.33 20.33 23.81 14.34 20.90 23.89 24.00 24.00 24.00 24.00
#> 62 12 82 156 112 152 75 98.1 67 137 151 165 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 185 156.1 132 19 176 80 191 64 47 138 98.2 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 28 122 11 3 120 165.1 46 119 160.1 156.2 138.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 143 173 122.1 87 46.1 172 54 147 162 118 119.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 182 116.1 119.2 74 38.1 12.1 27.1 75.1 35 74.1 53.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 143.1 141 64.1 161 53.2 148 143.2 186 53.3 138.2 1 138.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 17 135 131 178 74.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[3]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.000147673 0.712277084 0.300077516
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.16809509 0.02199252 0.10289107
#> grade_iii, Cure model
#> 0.48826285
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 123 13.00 1 44 1 0
#> 14 12.89 1 21 0 0
#> 199 19.81 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 194 22.40 1 38 0 1
#> 166 19.98 1 48 0 0
#> 139 21.49 1 63 1 0
#> 4 17.64 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 106 16.67 1 49 1 0
#> 195 11.76 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 128 20.35 1 35 0 1
#> 195.1 11.76 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 96 14.54 1 33 0 1
#> 56 12.21 1 60 0 0
#> 16 8.71 1 71 0 1
#> 76 19.22 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 41 18.02 1 40 1 0
#> 192 16.44 1 31 1 0
#> 145 10.07 1 65 1 0
#> 108 18.29 1 39 0 1
#> 166.1 19.98 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 79 16.23 1 54 1 0
#> 106.1 16.67 1 49 1 0
#> 93.1 10.33 1 52 0 1
#> 106.2 16.67 1 49 1 0
#> 123.1 13.00 1 44 1 0
#> 89 11.44 1 NA 0 0
#> 195.2 11.76 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 158 20.14 1 74 1 0
#> 63 22.77 1 31 1 0
#> 133 14.65 1 57 0 0
#> 29 15.45 1 68 1 0
#> 114.1 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 136 21.83 1 43 0 1
#> 166.2 19.98 1 48 0 0
#> 158.1 20.14 1 74 1 0
#> 169 22.41 1 46 0 0
#> 110 17.56 1 65 0 1
#> 15 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 123.2 13.00 1 44 1 0
#> 124.1 9.73 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 63.1 22.77 1 31 1 0
#> 25 6.32 1 34 1 0
#> 97.1 19.14 1 65 0 1
#> 25.1 6.32 1 34 1 0
#> 99 21.19 1 38 0 1
#> 59 10.16 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 179 18.63 1 42 0 0
#> 134 17.81 1 47 1 0
#> 55 19.34 1 69 0 1
#> 107 11.18 1 54 1 0
#> 114.2 13.68 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 6 15.64 1 39 0 0
#> 124.2 9.73 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 192.1 16.44 1 31 1 0
#> 113 22.86 1 34 0 0
#> 66 22.13 1 53 0 0
#> 169.1 22.41 1 46 0 0
#> 124.3 9.73 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 86 23.81 1 58 0 1
#> 79.1 16.23 1 54 1 0
#> 76.1 19.22 1 54 0 1
#> 36 21.19 1 48 0 1
#> 129 23.41 1 53 1 0
#> 29.1 15.45 1 68 1 0
#> 56.1 12.21 1 60 0 0
#> 49 12.19 1 48 1 0
#> 134.1 17.81 1 47 1 0
#> 106.3 16.67 1 49 1 0
#> 77 7.27 1 67 0 1
#> 136.1 21.83 1 43 0 1
#> 59.2 10.16 1 NA 1 0
#> 23.1 16.92 1 61 0 0
#> 25.2 6.32 1 34 1 0
#> 68 20.62 1 44 0 0
#> 136.2 21.83 1 43 0 1
#> 114.3 13.68 1 NA 0 0
#> 5 16.43 1 51 0 1
#> 29.2 15.45 1 68 1 0
#> 154 12.63 1 20 1 0
#> 158.2 20.14 1 74 1 0
#> 8 18.43 1 32 0 0
#> 99.1 21.19 1 38 0 1
#> 188 16.16 1 46 0 1
#> 168 23.72 1 70 0 0
#> 78 23.88 1 43 0 0
#> 68.1 20.62 1 44 0 0
#> 170 19.54 1 43 0 1
#> 59.3 10.16 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 57 14.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 86.1 23.81 1 58 0 1
#> 110.1 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 137 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 103 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 143 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 17 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 147 24.00 0 76 1 0
#> 115 24.00 0 NA 1 0
#> 104 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 118 24.00 0 44 1 0
#> 34.1 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 98 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 185 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 152 24.00 0 36 0 1
#> 95.1 24.00 0 68 0 1
#> 94 24.00 0 51 0 1
#> 138.1 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 116.1 24.00 0 58 0 1
#> 17.1 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 11 24.00 0 42 0 1
#> 174.1 24.00 0 49 1 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 87.1 24.00 0 27 0 0
#> 9.1 24.00 0 31 1 0
#> 64.2 24.00 0 43 0 0
#> 135 24.00 0 58 1 0
#> 198 24.00 0 66 0 1
#> 47 24.00 0 38 0 1
#> 1 24.00 0 23 1 0
#> 28 24.00 0 67 1 0
#> 95.2 24.00 0 68 0 1
#> 143.1 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 198.1 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 83 24.00 0 6 0 0
#> 144.1 24.00 0 28 0 1
#> 138.2 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 165.1 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 144.2 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 135.1 24.00 0 58 1 0
#> 165.2 24.00 0 47 0 0
#> 118.1 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 162.2 24.00 0 51 0 0
#> 174.2 24.00 0 49 1 0
#> 54.1 24.00 0 53 1 0
#> 21.1 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 151 24.00 0 42 0 0
#> 121.1 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 137.1 24.00 0 45 1 0
#> 80 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 47.1 24.00 0 38 0 1
#> 151.1 24.00 0 42 0 0
#> 112 24.00 0 61 0 0
#> 156.1 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.17 NA NA NA
#> 2 age, Cure model 0.0220 NA NA NA
#> 3 grade_ii, Cure model 0.103 NA NA NA
#> 4 grade_iii, Cure model 0.488 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000148 NA NA NA
#> 2 grade_ii, Survival model 0.712 NA NA NA
#> 3 grade_iii, Survival model 0.300 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16810 0.02199 0.10289 0.48826
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 250.6
#> Residual Deviance: 244.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16809509 0.02199252 0.10289107 0.48826285
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.000147673 0.712277084 0.300077516
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.84073067 0.86328229 0.93697873 0.23061169 0.43791016 0.31206728
#> [7] 0.79366054 0.65891248 0.63072487 0.38274370 0.39454883 0.81732843
#> [13] 0.89320995 0.96545936 0.50106116 0.80155034 0.58286915 0.70265836
#> [19] 0.95127659 0.56254458 0.43791016 0.88582775 0.72838786 0.65891248
#> [25] 0.93697873 0.65891248 0.84073067 0.57273991 0.40635148 0.15775141
#> [31] 0.80943971 0.76998016 0.52168639 0.25983534 0.43791016 0.40635148
#> [37] 0.20167426 0.61187734 0.18663418 0.64016882 0.87086571 0.84073067
#> [43] 0.92976249 0.15775141 0.97953052 0.52168639 0.97953052 0.32456103
#> [49] 0.91522918 0.54201995 0.59281676 0.48012519 0.92252602 0.48012519
#> [55] 0.75339036 0.95839575 0.70265836 0.13876871 0.24522681 0.20167426
#> [61] 0.76173293 0.05673525 0.72838786 0.50106116 0.32456103 0.11977704
#> [67] 0.76998016 0.89320995 0.90791120 0.59281676 0.65891248 0.97250419
#> [73] 0.25983534 0.64016882 0.97953052 0.35924295 0.25983534 0.71980162
#> [79] 0.76998016 0.87838001 0.40635148 0.55228272 0.32456103 0.74504726
#> [85] 0.09699483 0.02100427 0.35924295 0.46945367 0.81732843 0.83292293
#> [91] 0.29902124 0.05673525 0.61187734 0.69380607 0.00000000 0.00000000
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000
#>
#> $Time
#> 123 14 93 194 166 139 18 106 45 128 150 96 56
#> 13.00 12.89 10.33 22.40 19.98 21.49 15.21 16.67 17.42 20.35 20.33 14.54 12.21
#> 16 76 180 41 192 145 108 166.1 37 79 106.1 93.1 106.2
#> 8.71 19.22 14.82 18.02 16.44 10.07 18.29 19.98 12.52 16.23 16.67 10.33 16.67
#> 123.1 51 158 63 133 29 97 136 166.2 158.1 169 110 15
#> 13.00 18.23 20.14 22.77 14.65 15.45 19.14 21.83 19.98 20.14 22.41 17.56 22.68
#> 23 140 123.2 159 63.1 25 97.1 25.1 99 43 179 134 55
#> 16.92 12.68 13.00 10.55 22.77 6.32 19.14 6.32 21.19 12.10 18.63 17.81 19.34
#> 107 58 6 183 192.1 113 66 169.1 167 86 79.1 76.1 36
#> 11.18 19.34 15.64 9.24 16.44 22.86 22.13 22.41 15.55 23.81 16.23 19.22 21.19
#> 129 29.1 56.1 49 134.1 106.3 77 136.1 23.1 25.2 68 136.2 5
#> 23.41 15.45 12.21 12.19 17.81 16.67 7.27 21.83 16.92 6.32 20.62 21.83 16.43
#> 29.2 154 158.2 8 99.1 188 168 78 68.1 170 96.1 57 197
#> 15.45 12.63 20.14 18.43 21.19 16.16 23.72 23.88 20.62 19.54 14.54 14.46 21.60
#> 86.1 110.1 171 137 64 103 162 9 21 200 143 22 141
#> 23.81 17.56 16.57 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 17 34 156 87 147 104 162.1 186 196 118 34.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 144 98 160 116 174 185 95 165 152 95.1 94 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 116.1 17.1 53 191 11 174.1 121 35 3 33 87.1 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.2 135 198 47 1 28 95.2 143.1 142 198.1 54 83 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.2 27.1 165.1 67 144.2 173 135.1 165.2 118.1 147.1 162.2 174.2 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 7 151 121.1 11.1 137.1 80 119 47.1 151.1 112 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[4]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01084630 -0.05281149 -0.17183047
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.3823897 0.0105953 -0.1029624
#> grade_iii, Cure model
#> 0.3959931
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 36 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 41.1 18.02 1 40 1 0
#> 130 16.47 1 53 0 1
#> 181 16.46 1 45 0 1
#> 23 16.92 1 61 0 0
#> 29 15.45 1 68 1 0
#> 10 10.53 1 34 0 0
#> 45 17.42 1 54 0 1
#> 18 15.21 1 49 1 0
#> 13 14.34 1 54 0 1
#> 166 19.98 1 48 0 0
#> 183 9.24 1 67 1 0
#> 175 21.91 1 43 0 0
#> 99 21.19 1 38 0 1
#> 175.1 21.91 1 43 0 0
#> 123 13.00 1 44 1 0
#> 194 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 43 12.10 1 61 0 1
#> 10.1 10.53 1 34 0 0
#> 76 19.22 1 54 0 1
#> 40 18.00 1 28 1 0
#> 177 12.53 1 75 0 0
#> 15 22.68 1 48 0 0
#> 184 17.77 1 38 0 0
#> 170 19.54 1 43 0 1
#> 52 10.42 1 52 0 1
#> 96 14.54 1 33 0 1
#> 190 20.81 1 42 1 0
#> 149 8.37 1 33 1 0
#> 123.1 13.00 1 44 1 0
#> 51 18.23 1 83 0 1
#> 49 12.19 1 48 1 0
#> 154 12.63 1 20 1 0
#> 77 7.27 1 67 0 1
#> 100 16.07 1 60 0 0
#> 92 22.92 1 47 0 1
#> 60 13.15 1 38 1 0
#> 88 18.37 1 47 0 0
#> 23.1 16.92 1 61 0 0
#> 145 10.07 1 65 1 0
#> 129 23.41 1 53 1 0
#> 130.1 16.47 1 53 0 1
#> 56 12.21 1 60 0 0
#> 130.2 16.47 1 53 0 1
#> 171 16.57 1 41 0 1
#> 128 20.35 1 35 0 1
#> 184.1 17.77 1 38 0 0
#> 69 23.23 1 25 0 1
#> 29.1 15.45 1 68 1 0
#> 13.1 14.34 1 54 0 1
#> 134 17.81 1 47 1 0
#> 179 18.63 1 42 0 0
#> 63 22.77 1 31 1 0
#> 60.1 13.15 1 38 1 0
#> 61 10.12 1 36 0 1
#> 77.1 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 133 14.65 1 57 0 0
#> 100.1 16.07 1 60 0 0
#> 166.1 19.98 1 48 0 0
#> 40.1 18.00 1 28 1 0
#> 164 23.60 1 76 0 1
#> 133.1 14.65 1 57 0 0
#> 181.1 16.46 1 45 0 1
#> 77.2 7.27 1 67 0 1
#> 180 14.82 1 37 0 0
#> 189 10.51 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 61.1 10.12 1 36 0 1
#> 157.1 15.10 1 47 0 0
#> 26 15.77 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 99.2 21.19 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 169 22.41 1 46 0 0
#> 32 20.90 1 37 1 0
#> 5 16.43 1 51 0 1
#> 124 9.73 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 70 7.38 1 30 1 0
#> 157.2 15.10 1 47 0 0
#> 175.2 21.91 1 43 0 0
#> 66 22.13 1 53 0 0
#> 63.1 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 26.1 15.77 1 49 0 1
#> 190.1 20.81 1 42 1 0
#> 157.3 15.10 1 47 0 0
#> 164.1 23.60 1 76 0 1
#> 32.1 20.90 1 37 1 0
#> 92.1 22.92 1 47 0 1
#> 66.1 22.13 1 53 0 0
#> 164.2 23.60 1 76 0 1
#> 79 16.23 1 54 1 0
#> 5.1 16.43 1 51 0 1
#> 154.1 12.63 1 20 1 0
#> 60.2 13.15 1 38 1 0
#> 8 18.43 1 32 0 0
#> 130.3 16.47 1 53 0 1
#> 129.1 23.41 1 53 1 0
#> 124.1 9.73 1 NA 1 0
#> 154.2 12.63 1 20 1 0
#> 79.1 16.23 1 54 1 0
#> 58 19.34 1 39 0 0
#> 129.2 23.41 1 53 1 0
#> 153 21.33 1 55 1 0
#> 125 15.65 1 67 1 0
#> 170.1 19.54 1 43 0 1
#> 3 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 73 24.00 0 NA 0 1
#> 147 24.00 0 76 1 0
#> 54 24.00 0 53 1 0
#> 33 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 87.1 24.00 0 27 0 0
#> 3.1 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 35 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 95 24.00 0 68 0 1
#> 44.1 24.00 0 56 0 0
#> 9.1 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 144 24.00 0 28 0 1
#> 162 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 84 24.00 0 39 0 1
#> 33.2 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 3.2 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 27 24.00 0 63 1 0
#> 74 24.00 0 43 0 1
#> 44.2 24.00 0 56 0 0
#> 104 24.00 0 50 1 0
#> 191.1 24.00 0 60 0 1
#> 7 24.00 0 37 1 0
#> 22 24.00 0 52 1 0
#> 144.1 24.00 0 28 0 1
#> 200 24.00 0 64 0 0
#> 185.1 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 47 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 147.1 24.00 0 76 1 0
#> 178 24.00 0 52 1 0
#> 44.3 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 74.1 24.00 0 43 0 1
#> 7.1 24.00 0 37 1 0
#> 141.2 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 44.4 24.00 0 56 0 0
#> 87.2 24.00 0 27 0 0
#> 44.5 24.00 0 56 0 0
#> 47.1 24.00 0 38 0 1
#> 84.1 24.00 0 39 0 1
#> 20 24.00 0 46 1 0
#> 9.2 24.00 0 31 1 0
#> 47.2 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 7.2 24.00 0 37 1 0
#> 172 24.00 0 41 0 0
#> 95.1 24.00 0 68 0 1
#> 47.3 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 84.2 24.00 0 39 0 1
#> 75.1 24.00 0 21 1 0
#> 185.2 24.00 0 44 1 0
#> 54.1 24.00 0 53 1 0
#> 182 24.00 0 35 0 0
#> 74.2 24.00 0 43 0 1
#> 48.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.382 NA NA NA
#> 2 age, Cure model 0.0106 NA NA NA
#> 3 grade_ii, Cure model -0.103 NA NA NA
#> 4 grade_iii, Cure model 0.396 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0108 NA NA NA
#> 2 grade_ii, Survival model -0.0528 NA NA NA
#> 3 grade_iii, Survival model -0.172 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.3824 0.0106 -0.1030 0.3960
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 262.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.3823897 0.0105953 -0.1029624 0.3959931
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01084630 -0.05281149 -0.17183047
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0634637055 0.1956643085 0.1956643085 0.2928821060 0.3320213046
#> [6] 0.2646824699 0.4541990136 0.8082704647 0.2555321100 0.4785156730
#> [11] 0.6071121144 0.1213938693 0.9017505989 0.0366521691 0.0634637055
#> [16] 0.0366521691 0.6763731171 0.0254130931 0.4909744293 0.7930165535
#> [21] 0.8082704647 0.1564502881 0.2121947116 0.7481396332 0.0187715380
#> [26] 0.2378885670 0.1348942005 0.8388430449 0.5802728629 0.0959704439
#> [31] 0.9178771841 0.6763731171 0.1874891331 0.7779267730 0.7050091836
#> [36] 0.9504115926 0.3963032331 0.0083663279 0.6345968668 0.1795418876
#> [41] 0.2646824699 0.8857786524 0.0020515371 0.2928821060 0.7629636647
#> [46] 0.2928821060 0.2832786565 0.1147540293 0.2378885670 0.0062080267
#> [51] 0.4541990136 0.6071121144 0.2291210174 0.1640263663 0.0132315187
#> [56] 0.6345968668 0.8544204562 0.9504115926 0.0487935709 0.5539347304
#> [61] 0.3963032331 0.1213938693 0.2121947116 0.0001367986 0.5539347304
#> [66] 0.3320213046 0.9504115926 0.5408947695 0.0634637055 0.8544204562
#> [71] 0.4909744293 0.4189480312 0.0634637055 0.0219936331 0.0842667715
#> [76] 0.3528152165 0.5802728629 0.9340997812 0.4909744293 0.0366521691
#> [81] 0.0290494184 0.0132315187 0.0534667022 0.1082732017 0.4189480312
#> [86] 0.0959704439 0.4909744293 0.0001367986 0.0842667715 0.0083663279
#> [91] 0.0290494184 0.0001367986 0.3742610987 0.3528152165 0.7050091836
#> [96] 0.6345968668 0.1717327238 0.2928821060 0.0020515371 0.7050091836
#> [101] 0.3742610987 0.1490642274 0.0020515371 0.0583629446 0.4422285136
#> [106] 0.1348942005 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 36 41 41.1 130 181 23 29 10 45 18 13 166 183
#> 21.19 18.02 18.02 16.47 16.46 16.92 15.45 10.53 17.42 15.21 14.34 19.98 9.24
#> 175 99 175.1 123 194 157 43 10.1 76 40 177 15 184
#> 21.91 21.19 21.91 13.00 22.40 15.10 12.10 10.53 19.22 18.00 12.53 22.68 17.77
#> 170 52 96 190 149 123.1 51 49 154 77 100 92 60
#> 19.54 10.42 14.54 20.81 8.37 13.00 18.23 12.19 12.63 7.27 16.07 22.92 13.15
#> 88 23.1 145 129 130.1 56 130.2 171 128 184.1 69 29.1 13.1
#> 18.37 16.92 10.07 23.41 16.47 12.21 16.47 16.57 20.35 17.77 23.23 15.45 14.34
#> 134 179 63 60.1 61 77.1 197 133 100.1 166.1 40.1 164 133.1
#> 17.81 18.63 22.77 13.15 10.12 7.27 21.60 14.65 16.07 19.98 18.00 23.60 14.65
#> 181.1 77.2 180 99.1 61.1 157.1 26 99.2 169 32 5 96.1 70
#> 16.46 7.27 14.82 21.19 10.12 15.10 15.77 21.19 22.41 20.90 16.43 14.54 7.38
#> 157.2 175.2 66 63.1 139 68 26.1 190.1 157.3 164.1 32.1 92.1 66.1
#> 15.10 21.91 22.13 22.77 21.49 20.62 15.77 20.81 15.10 23.60 20.90 22.92 22.13
#> 164.2 79 5.1 154.1 60.2 8 130.3 129.1 154.2 79.1 58 129.2 153
#> 23.60 16.23 16.43 12.63 13.15 18.43 16.47 23.41 12.63 16.23 19.34 23.41 21.33
#> 125 170.1 3 112 147 54 33 33.1 87 87.1 3.1 44 116
#> 15.65 19.54 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 19 9 141 34 35 1 95 44.1 9.1 98 191 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 144 162 116.1 138 141.1 94 84 33.2 198 137 75 3.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 135 27 74 44.2 104 191.1 7 22 144.1 200 185.1 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 143 160 160.1 80 109 147.1 178 44.3 46 74.1 7.1 141.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 44.4 87.2 44.5 47.1 84.1 20 9.2 47.2 48 138.1 7.2 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 47.3 193 71 84.2 75.1 185.2 54.1 182 74.2 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[5]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0003100529 0.9717295761 0.5059625865
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.53760875 0.02703706 0.09885833
#> grade_iii, Cure model
#> 1.39768849
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 158 20.14 1 74 1 0
#> 187 9.92 1 39 1 0
#> 125 15.65 1 67 1 0
#> 155 13.08 1 26 0 0
#> 139 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 55 19.34 1 69 0 1
#> 39.1 15.59 1 37 0 1
#> 184 17.77 1 38 0 0
#> 194 22.40 1 38 0 1
#> 177 12.53 1 75 0 0
#> 127 3.53 1 62 0 1
#> 105 19.75 1 60 0 0
#> 177.1 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 110 17.56 1 65 0 1
#> 78 23.88 1 43 0 0
#> 183 9.24 1 67 1 0
#> 111 17.45 1 47 0 1
#> 188 16.16 1 46 0 1
#> 175.1 21.91 1 43 0 0
#> 89 11.44 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 114 13.68 1 NA 0 0
#> 123 13.00 1 44 1 0
#> 179 18.63 1 42 0 0
#> 145 10.07 1 65 1 0
#> 175.2 21.91 1 43 0 0
#> 140 12.68 1 59 1 0
#> 56 12.21 1 60 0 0
#> 79 16.23 1 54 1 0
#> 32 20.90 1 37 1 0
#> 10 10.53 1 34 0 0
#> 91 5.33 1 61 0 1
#> 69 23.23 1 25 0 1
#> 69.1 23.23 1 25 0 1
#> 18 15.21 1 49 1 0
#> 194.1 22.40 1 38 0 1
#> 78.1 23.88 1 43 0 0
#> 23 16.92 1 61 0 0
#> 49 12.19 1 48 1 0
#> 99 21.19 1 38 0 1
#> 49.1 12.19 1 48 1 0
#> 45 17.42 1 54 0 1
#> 89.1 11.44 1 NA 0 0
#> 180 14.82 1 37 0 0
#> 195 11.76 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 43 12.10 1 61 0 1
#> 180.1 14.82 1 37 0 0
#> 167 15.55 1 56 1 0
#> 133 14.65 1 57 0 0
#> 100 16.07 1 60 0 0
#> 192 16.44 1 31 1 0
#> 134 17.81 1 47 1 0
#> 55.1 19.34 1 69 0 1
#> 30 17.43 1 78 0 0
#> 70 7.38 1 30 1 0
#> 164 23.60 1 76 0 1
#> 96.1 14.54 1 33 0 1
#> 96.2 14.54 1 33 0 1
#> 159.1 10.55 1 50 0 1
#> 81 14.06 1 34 0 0
#> 159.2 10.55 1 50 0 1
#> 192.1 16.44 1 31 1 0
#> 188.1 16.16 1 46 0 1
#> 70.1 7.38 1 30 1 0
#> 66 22.13 1 53 0 0
#> 159.3 10.55 1 50 0 1
#> 50 10.02 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 183.1 9.24 1 67 1 0
#> 97 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 145.1 10.07 1 65 1 0
#> 189 10.51 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 164.1 23.60 1 76 0 1
#> 168 23.72 1 70 0 0
#> 39.2 15.59 1 37 0 1
#> 68.1 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 127.1 3.53 1 62 0 1
#> 61 10.12 1 36 0 1
#> 192.2 16.44 1 31 1 0
#> 136 21.83 1 43 0 1
#> 136.1 21.83 1 43 0 1
#> 52.1 10.42 1 52 0 1
#> 58 19.34 1 39 0 0
#> 39.3 15.59 1 37 0 1
#> 166 19.98 1 48 0 0
#> 57 14.46 1 45 0 1
#> 134.1 17.81 1 47 1 0
#> 77 7.27 1 67 0 1
#> 16.1 8.71 1 71 0 1
#> 183.2 9.24 1 67 1 0
#> 123.1 13.00 1 44 1 0
#> 117 17.46 1 26 0 1
#> 157 15.10 1 47 0 0
#> 50.1 10.02 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 159.4 10.55 1 50 0 1
#> 57.1 14.46 1 45 0 1
#> 15 22.68 1 48 0 0
#> 99.1 21.19 1 38 0 1
#> 55.2 19.34 1 69 0 1
#> 159.5 10.55 1 50 0 1
#> 26 15.77 1 49 0 1
#> 5 16.43 1 51 0 1
#> 66.1 22.13 1 53 0 0
#> 152 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 152.1 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 109 24.00 0 48 0 0
#> 152.2 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 182 24.00 0 35 0 0
#> 185 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 182.1 24.00 0 35 0 0
#> 141 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 182.2 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 9.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 82 24.00 0 34 0 0
#> 160 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 11.1 24.00 0 42 0 1
#> 3 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 80.1 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 19 24.00 0 57 0 1
#> 3.1 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 163 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 71 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 142.1 24.00 0 53 0 0
#> 144.1 24.00 0 28 0 1
#> 73 24.00 0 NA 0 1
#> 126 24.00 0 48 0 0
#> 200.1 24.00 0 64 0 0
#> 44.1 24.00 0 56 0 0
#> 132 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 9.2 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 137.1 24.00 0 45 1 0
#> 137.2 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 48.1 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 82.1 24.00 0 34 0 0
#> 198 24.00 0 66 0 1
#> 121.1 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 87.1 24.00 0 27 0 0
#> 9.3 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 156.1 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 44.2 24.00 0 56 0 0
#> 34.1 24.00 0 36 0 0
#> 173.1 24.00 0 19 0 1
#> 9.4 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 9.5 24.00 0 31 1 0
#> 200.2 24.00 0 64 0 0
#> 9.6 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 7 24.00 0 37 1 0
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 116 24.00 0 58 0 1
#> 87.2 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 33.1 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 151 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.54 NA NA NA
#> 2 age, Cure model 0.0270 NA NA NA
#> 3 grade_ii, Cure model 0.0989 NA NA NA
#> 4 grade_iii, Cure model 1.40 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000310 NA NA NA
#> 2 grade_ii, Survival model 0.972 NA NA NA
#> 3 grade_iii, Survival model 0.506 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.53761 0.02704 0.09886 1.39769
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 240.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.53760875 0.02703706 0.09885833 1.39768849
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0003100529 0.9717295761 0.5059625865
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.66584918 0.38968008 0.93252131 0.65813993 0.78040029 0.31863882
#> [7] 0.84689719 0.43330891 0.66584918 0.52158309 0.19148270 0.80753402
#> [13] 0.98905507 0.41159711 0.80753402 0.24952487 0.53098920 0.02801744
#> [19] 0.93843655 0.54946736 0.62657462 0.24952487 0.73854821 0.78737329
#> [25] 0.48284807 0.90857964 0.24952487 0.80085833 0.82082507 0.61850070
#> [31] 0.35546235 0.88379518 0.98352499 0.14229454 0.14229454 0.70258447
#> [37] 0.19148270 0.02801744 0.57660846 0.82749669 0.33149105 0.82749669
#> [43] 0.56762837 0.71700238 0.36699535 0.92060213 0.84043660 0.71700238
#> [49] 0.69524828 0.73134344 0.64234293 0.58558589 0.50293654 0.43330891
#> [55] 0.55854967 0.96685800 0.10433251 0.73854821 0.73854821 0.84689719
#> [61] 0.77342679 0.84689719 0.58558589 0.62657462 0.96685800 0.22053260
#> [67] 0.84689719 0.92060213 0.93843655 0.47280008 0.49289332 0.90857964
#> [73] 0.95552544 0.10433251 0.07515731 0.66584918 0.36699535 0.89005417
#> [79] 0.98905507 0.90240943 0.58558589 0.29164619 0.29164619 0.89005417
#> [85] 0.43330891 0.66584918 0.40064083 0.75954136 0.50293654 0.97797337
#> [91] 0.95552544 0.93843655 0.78737329 0.54028136 0.70979396 0.42254793
#> [97] 0.84689719 0.75954136 0.17455339 0.33149105 0.43330891 0.84689719
#> [103] 0.65027424 0.61024496 0.22053260 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 39 158 187 125 155 139 159 55 39.1 184 194 177 127
#> 15.59 20.14 9.92 15.65 13.08 21.49 10.55 19.34 15.59 17.77 22.40 12.53 3.53
#> 105 177.1 175 110 78 183 111 188 175.1 96 123 179 145
#> 19.75 12.53 21.91 17.56 23.88 9.24 17.45 16.16 21.91 14.54 13.00 18.63 10.07
#> 175.2 140 56 79 32 10 91 69 69.1 18 194.1 78.1 23
#> 21.91 12.68 12.21 16.23 20.90 10.53 5.33 23.23 23.23 15.21 22.40 23.88 16.92
#> 49 99 49.1 45 180 68 101 43 180.1 167 133 100 192
#> 12.19 21.19 12.19 17.42 14.82 20.62 9.97 12.10 14.82 15.55 14.65 16.07 16.44
#> 134 55.1 30 70 164 96.1 96.2 159.1 81 159.2 192.1 188.1 70.1
#> 17.81 19.34 17.43 7.38 23.60 14.54 14.54 10.55 14.06 10.55 16.44 16.16 7.38
#> 66 159.3 101.1 183.1 97 8 145.1 16 164.1 168 39.2 68.1 52
#> 22.13 10.55 9.97 9.24 19.14 18.43 10.07 8.71 23.60 23.72 15.59 20.62 10.42
#> 127.1 61 192.2 136 136.1 52.1 58 39.3 166 57 134.1 77 16.1
#> 3.53 10.12 16.44 21.83 21.83 10.42 19.34 15.59 19.98 14.46 17.81 7.27 8.71
#> 183.2 123.1 117 157 170 159.4 57.1 15 99.1 55.2 159.5 26 5
#> 9.24 13.00 17.46 15.10 19.54 10.55 14.46 22.68 21.19 19.34 10.55 15.77 16.43
#> 66.1 152 95 48 9 137 11 152.1 142 109 152.2 44 182
#> 22.13 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 200 182.1 141 112 161 156 182.2 121 9.1 87 82 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 11.1 3 80 80.1 144 19 3.1 34 163 75 71 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 144.1 126 200.1 44.1 132 38 122 191 9.2 173 137.1 137.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 33 21 48.1 62 147 82.1 198 121.1 65 1 87.1 9.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 64 156.1 143 44.2 34.1 173.1 9.4 9.5 200.2 9.6 176 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 67 116 87.2 35 148 33.1 94 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[6]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004046555 0.704108905 0.251124055
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.35044449 -0.00146985 0.82468264
#> grade_iii, Cure model
#> 1.11756954
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 37 12.52 1 57 1 0
#> 32 20.90 1 37 1 0
#> 187 9.92 1 39 1 0
#> 25 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 168 23.72 1 70 0 0
#> 197 21.60 1 69 1 0
#> 157 15.10 1 47 0 0
#> 134.1 17.81 1 47 1 0
#> 154 12.63 1 20 1 0
#> 18 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 154.1 12.63 1 20 1 0
#> 58 19.34 1 39 0 0
#> 183 9.24 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 157.1 15.10 1 47 0 0
#> 51 18.23 1 83 0 1
#> 50 10.02 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 85 16.44 1 36 0 0
#> 50.1 10.02 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 8 18.43 1 32 0 0
#> 81 14.06 1 34 0 0
#> 127 3.53 1 62 0 1
#> 88.1 18.37 1 47 0 0
#> 123 13.00 1 44 1 0
#> 56 12.21 1 60 0 0
#> 111 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 188 16.16 1 46 0 1
#> 113 22.86 1 34 0 0
#> 13 14.34 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 199 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 129 23.41 1 53 1 0
#> 181 16.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 145 10.07 1 65 1 0
#> 101 9.97 1 10 0 1
#> 134.2 17.81 1 47 1 0
#> 13.1 14.34 1 54 0 1
#> 111.1 17.45 1 47 0 1
#> 177 12.53 1 75 0 0
#> 145.1 10.07 1 65 1 0
#> 195 11.76 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 4 17.64 1 NA 0 1
#> 49 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 24 23.89 1 38 0 0
#> 167 15.55 1 56 1 0
#> 175 21.91 1 43 0 0
#> 37.1 12.52 1 57 1 0
#> 192.1 16.44 1 31 1 0
#> 164.1 23.60 1 76 0 1
#> 194 22.40 1 38 0 1
#> 159 10.55 1 50 0 1
#> 45 17.42 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 6 15.64 1 39 0 0
#> 18.1 15.21 1 49 1 0
#> 13.2 14.34 1 54 0 1
#> 127.1 3.53 1 62 0 1
#> 15 22.68 1 48 0 0
#> 36.1 21.19 1 48 0 1
#> 5 16.43 1 51 0 1
#> 167.1 15.55 1 56 1 0
#> 68 20.62 1 44 0 0
#> 81.1 14.06 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 30 17.43 1 78 0 0
#> 51.2 18.23 1 83 0 1
#> 194.1 22.40 1 38 0 1
#> 92 22.92 1 47 0 1
#> 51.3 18.23 1 83 0 1
#> 181.1 16.46 1 45 0 1
#> 36.2 21.19 1 48 0 1
#> 155 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 49.1 12.19 1 48 1 0
#> 52 10.42 1 52 0 1
#> 79.1 16.23 1 54 1 0
#> 91 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 76 19.22 1 54 0 1
#> 42 12.43 1 49 0 1
#> 85.1 16.44 1 36 0 0
#> 179 18.63 1 42 0 0
#> 49.2 12.19 1 48 1 0
#> 106 16.67 1 49 1 0
#> 57 14.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 90 20.94 1 50 0 1
#> 16 8.71 1 71 0 1
#> 140 12.68 1 59 1 0
#> 194.2 22.40 1 38 0 1
#> 150 20.33 1 48 0 0
#> 123.1 13.00 1 44 1 0
#> 25.1 6.32 1 34 1 0
#> 39.1 15.59 1 37 0 1
#> 123.2 13.00 1 44 1 0
#> 58.1 19.34 1 39 0 0
#> 187.1 9.92 1 39 1 0
#> 61 10.12 1 36 0 1
#> 6.1 15.64 1 39 0 0
#> 9 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 53 24.00 0 32 0 1
#> 46 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 191 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 198 24.00 0 66 0 1
#> 31 24.00 0 36 0 1
#> 33.1 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 132 24.00 0 55 0 0
#> 131.1 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 137 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 116.1 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 174 24.00 0 49 1 0
#> 144 24.00 0 28 0 1
#> 178 24.00 0 52 1 0
#> 132.1 24.00 0 55 0 0
#> 122.1 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 198.1 24.00 0 66 0 1
#> 178.1 24.00 0 52 1 0
#> 31.1 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 135 24.00 0 58 1 0
#> 121.1 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 148.1 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 11 24.00 0 42 0 1
#> 33.2 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 144.1 24.00 0 28 0 1
#> 132.2 24.00 0 55 0 0
#> 116.2 24.00 0 58 0 1
#> 161 24.00 0 45 0 0
#> 34.1 24.00 0 36 0 0
#> 19 24.00 0 57 0 1
#> 102 24.00 0 49 0 0
#> 178.2 24.00 0 52 1 0
#> 3 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 173 24.00 0 19 0 1
#> 156 24.00 0 50 1 0
#> 198.2 24.00 0 66 0 1
#> 156.1 24.00 0 50 1 0
#> 161.1 24.00 0 45 0 0
#> 3.1 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 2.1 24.00 0 9 0 0
#> 143.1 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 147 24.00 0 76 1 0
#> 102.2 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 35.2 24.00 0 51 0 0
#> 34.2 24.00 0 36 0 0
#> 119 24.00 0 17 0 0
#> 71 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#> 82.1 24.00 0 34 0 0
#> 9.1 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 172.1 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.350 NA NA NA
#> 2 age, Cure model -0.00147 NA NA NA
#> 3 grade_ii, Cure model 0.825 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00405 NA NA NA
#> 2 grade_ii, Survival model 0.704 NA NA NA
#> 3 grade_iii, Survival model 0.251 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.35044 -0.00147 0.82468 1.11757
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 252.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.35044449 -0.00146985 0.82468264 1.11756954
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004046555 0.704108905 0.251124055
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.408215958 0.814467498 0.235675426 0.929111772 0.960893819 0.326743867
#> [7] 0.017939320 0.174375566 0.667141248 0.408215958 0.789238746 0.649670894
#> [13] 0.559311293 0.789238746 0.265836529 0.945004272 0.195767056 0.667141248
#> [19] 0.357730428 0.108873611 0.513639553 0.436786396 0.306392723 0.728533526
#> [25] 0.984370081 0.326743867 0.754992014 0.839424872 0.446491428 0.347317293
#> [31] 0.577414524 0.096415288 0.702378803 0.306392723 0.586528555 0.059089734
#> [37] 0.494686079 0.185262097 0.904905371 0.921030345 0.408215958 0.702378803
#> [43] 0.446491428 0.806013082 0.904905371 0.033374980 0.847786839 0.513639553
#> [49] 0.005588849 0.631885721 0.163117275 0.814467498 0.513639553 0.033374980
#> [55] 0.131939967 0.872151432 0.475367917 0.357730428 0.071799811 0.595634911
#> [61] 0.649670894 0.702378803 0.984370081 0.120308857 0.195767056 0.549995204
#> [67] 0.631885721 0.245661234 0.728533526 0.684691220 0.465638945 0.357730428
#> [73] 0.131939967 0.084162373 0.357730428 0.494686079 0.195767056 0.746130520
#> [79] 0.613788855 0.847786839 0.880345936 0.559311293 0.976523825 0.888537273
#> [85] 0.285916260 0.831080824 0.513639553 0.296126815 0.847786839 0.485090301
#> [91] 0.693539041 0.397967997 0.225366111 0.952947868 0.780647781 0.131939967
#> [97] 0.255713734 0.754992014 0.960893819 0.613788855 0.754992014 0.265836529
#> [103] 0.929111772 0.896725475 0.595634911 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 134 37 32 187 25 88 168 197 157 134.1 154 18 79
#> 17.81 12.52 20.90 9.92 6.32 18.37 23.72 21.60 15.10 17.81 12.63 15.21 16.23
#> 154.1 58 183 36 157.1 51 63 85 117 8 81 127 88.1
#> 12.63 19.34 9.24 21.19 15.10 18.23 22.77 16.44 17.46 18.43 14.06 3.53 18.37
#> 123 56 111 108 188 113 13 8.1 26 129 181 153 145
#> 13.00 12.21 17.45 18.29 16.16 22.86 14.34 18.43 15.77 23.41 16.46 21.33 10.07
#> 101 134.2 13.1 111.1 177 145.1 164 49 192 24 167 175 37.1
#> 9.97 17.81 14.34 17.45 12.53 10.07 23.60 12.19 16.44 23.89 15.55 21.91 12.52
#> 192.1 164.1 194 159 45 51.1 69 6 18.1 13.2 127.1 15 36.1
#> 16.44 23.60 22.40 10.55 17.42 18.23 23.23 15.64 15.21 14.34 3.53 22.68 21.19
#> 5 167.1 68 81.1 180 30 51.2 194.1 92 51.3 181.1 36.2 155
#> 16.43 15.55 20.62 14.06 14.82 17.43 18.23 22.40 22.92 18.23 16.46 21.19 13.08
#> 39 49.1 52 79.1 91 93 76 42 85.1 179 49.2 106 57
#> 15.59 12.19 10.42 16.23 5.33 10.33 19.22 12.43 16.44 18.63 12.19 16.67 14.46
#> 40 90 16 140 194.2 150 123.1 25.1 39.1 123.2 58.1 187.1 61
#> 18.00 20.94 8.71 12.68 22.40 20.33 13.00 6.32 15.59 13.00 19.34 9.92 10.12
#> 6.1 9 53 46 33 104 35 44 191 131 12 198 31
#> 15.64 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 116 132 131.1 2 137 121 82 109 116.1 120 34 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 94 174 144 178 132.1 122.1 141 172 126 198.1 178.1 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 135 121.1 151 162 35.1 160 112 148.1 152 11 33.2 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 144.1 132.2 116.2 161 34.1 19 102 178.2 3 152.1 95 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 156 198.2 156.1 161.1 3.1 102.1 2.1 143.1 147 102.2 1 35.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 119 71 137.1 82.1 9.1 182 172.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[7]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00219808 0.52957798 -0.31493014
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.549165727 0.004798144 0.535308485
#> grade_iii, Cure model
#> 0.820288236
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 155 13.08 1 26 0 0
#> 81 14.06 1 34 0 0
#> 158 20.14 1 74 1 0
#> 157 15.10 1 47 0 0
#> 111 17.45 1 47 0 1
#> 36 21.19 1 48 0 1
#> 183 9.24 1 67 1 0
#> 128 20.35 1 35 0 1
#> 149 8.37 1 33 1 0
#> 108 18.29 1 39 0 1
#> 190 20.81 1 42 1 0
#> 140 12.68 1 59 1 0
#> 8 18.43 1 32 0 0
#> 36.1 21.19 1 48 0 1
#> 180 14.82 1 37 0 0
#> 13 14.34 1 54 0 1
#> 29 15.45 1 68 1 0
#> 91 5.33 1 61 0 1
#> 128.1 20.35 1 35 0 1
#> 96 14.54 1 33 0 1
#> 51 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 167 15.55 1 56 1 0
#> 108.1 18.29 1 39 0 1
#> 145 10.07 1 65 1 0
#> 60 13.15 1 38 1 0
#> 10 10.53 1 34 0 0
#> 190.1 20.81 1 42 1 0
#> 89 11.44 1 NA 0 0
#> 36.2 21.19 1 48 0 1
#> 69 23.23 1 25 0 1
#> 199 19.81 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 128.2 20.35 1 35 0 1
#> 111.1 17.45 1 47 0 1
#> 155.1 13.08 1 26 0 0
#> 63 22.77 1 31 1 0
#> 45 17.42 1 54 0 1
#> 154 12.63 1 20 1 0
#> 29.1 15.45 1 68 1 0
#> 175 21.91 1 43 0 0
#> 167.1 15.55 1 56 1 0
#> 124 9.73 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 159 10.55 1 50 0 1
#> 6 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 59 10.16 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 100 16.07 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 167.2 15.55 1 56 1 0
#> 150 20.33 1 48 0 0
#> 69.1 23.23 1 25 0 1
#> 140.1 12.68 1 59 1 0
#> 195 11.76 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 79 16.23 1 54 1 0
#> 199.2 19.81 1 NA 0 1
#> 58 19.34 1 39 0 0
#> 181 16.46 1 45 0 1
#> 199.3 19.81 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 92 22.92 1 47 0 1
#> 68 20.62 1 44 0 0
#> 177 12.53 1 75 0 0
#> 155.2 13.08 1 26 0 0
#> 15.1 22.68 1 48 0 0
#> 179 18.63 1 42 0 0
#> 158.1 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 45.1 17.42 1 54 0 1
#> 140.2 12.68 1 59 1 0
#> 89.1 11.44 1 NA 0 0
#> 51.1 18.23 1 83 0 1
#> 179.1 18.63 1 42 0 0
#> 51.2 18.23 1 83 0 1
#> 113 22.86 1 34 0 0
#> 60.1 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 16 8.71 1 71 0 1
#> 59.1 10.16 1 NA 1 0
#> 89.2 11.44 1 NA 0 0
#> 107.1 11.18 1 54 1 0
#> 96.1 14.54 1 33 0 1
#> 134 17.81 1 47 1 0
#> 58.1 19.34 1 39 0 0
#> 8.1 18.43 1 32 0 0
#> 57 14.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 88 18.37 1 47 0 0
#> 100.1 16.07 1 60 0 0
#> 166 19.98 1 48 0 0
#> 30.1 17.43 1 78 0 0
#> 89.3 11.44 1 NA 0 0
#> 164.2 23.60 1 76 0 1
#> 18.1 15.21 1 49 1 0
#> 43 12.10 1 61 0 1
#> 134.1 17.81 1 47 1 0
#> 39 15.59 1 37 0 1
#> 181.1 16.46 1 45 0 1
#> 199.4 19.81 1 NA 0 1
#> 159.1 10.55 1 50 0 1
#> 171 16.57 1 41 0 1
#> 133 14.65 1 57 0 0
#> 45.2 17.42 1 54 0 1
#> 43.1 12.10 1 61 0 1
#> 79.1 16.23 1 54 1 0
#> 46 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 28 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 35 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 95 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 80 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 27 24.00 0 63 1 0
#> 28.1 24.00 0 67 1 0
#> 126 24.00 0 48 0 0
#> 162 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 7 24.00 0 37 1 0
#> 148 24.00 0 61 1 0
#> 161.1 24.00 0 45 0 0
#> 64 24.00 0 43 0 0
#> 104 24.00 0 50 1 0
#> 151 24.00 0 42 0 0
#> 7.1 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 126.1 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 95.1 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 64.1 24.00 0 43 0 0
#> 160 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 198.1 24.00 0 66 0 1
#> 138 24.00 0 44 1 0
#> 198.2 24.00 0 66 0 1
#> 74 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 75 24.00 0 21 1 0
#> 47 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 102 24.00 0 49 0 0
#> 33 24.00 0 53 0 0
#> 95.2 24.00 0 68 0 1
#> 31 24.00 0 36 0 1
#> 152 24.00 0 36 0 1
#> 74.1 24.00 0 43 0 1
#> 182.2 24.00 0 35 0 0
#> 7.2 24.00 0 37 1 0
#> 102.1 24.00 0 49 0 0
#> 120.1 24.00 0 68 0 1
#> 126.2 24.00 0 48 0 0
#> 75.1 24.00 0 21 1 0
#> 87.1 24.00 0 27 0 0
#> 20 24.00 0 46 1 0
#> 33.1 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 27.1 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 64.2 24.00 0 43 0 0
#> 67 24.00 0 25 0 0
#> 116 24.00 0 58 0 1
#> 165 24.00 0 47 0 0
#> 98 24.00 0 34 1 0
#> 48 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 72.1 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 196.1 24.00 0 19 0 0
#> 162.1 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 87.2 24.00 0 27 0 0
#> 147 24.00 0 76 1 0
#> 44.1 24.00 0 56 0 0
#> 109 24.00 0 48 0 0
#> 116.1 24.00 0 58 0 1
#> 82 24.00 0 34 0 0
#> 174.1 24.00 0 49 1 0
#> 19.1 24.00 0 57 0 1
#> 119 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 198.3 24.00 0 66 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.549 NA NA NA
#> 2 age, Cure model 0.00480 NA NA NA
#> 3 grade_ii, Cure model 0.535 NA NA NA
#> 4 grade_iii, Cure model 0.820 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00220 NA NA NA
#> 2 grade_ii, Survival model 0.530 NA NA NA
#> 3 grade_iii, Survival model -0.315 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.549166 0.004798 0.535308 0.820288
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 256
#> Residual Deviance: 249.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.549165727 0.004798144 0.535308485 0.820288236
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00219808 0.52957798 -0.31493014
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.93816600 0.77116900 0.73907343 0.19465431 0.66423154 0.37948874
#> [7] 0.09583376 0.94853413 0.15454436 0.96920722 0.30556148 0.12561356
#> [13] 0.80286642 0.27481407 0.09583376 0.67483856 0.72821951 0.62184120
#> [19] 0.98973128 0.15454436 0.69609808 0.32645799 0.40090023 0.58954200
#> [25] 0.30556148 0.92773347 0.74993884 0.91724525 0.12561356 0.09583376
#> [31] 0.01949991 0.46660037 0.15454436 0.37948874 0.77116900 0.05757755
#> [37] 0.42249367 0.83396051 0.62184120 0.08587756 0.58954200 0.64321958
#> [43] 0.89640581 0.56704362 0.06730374 0.45534178 0.22424876 0.54487427
#> [49] 0.58954200 0.18414568 0.01949991 0.80286642 0.00386177 0.52281591
#> [55] 0.23445449 0.48892287 0.00386177 0.03618995 0.14463571 0.84437482
#> [61] 0.77116900 0.06730374 0.25456336 0.19465431 0.87573273 0.42249367
#> [67] 0.80286642 0.32645799 0.25456336 0.32645799 0.04679074 0.74993884
#> [73] 0.51142102 0.95884974 0.87573273 0.69609808 0.35848254 0.23445449
#> [79] 0.27481407 0.71742222 0.97950095 0.29516728 0.54487427 0.21419678
#> [85] 0.40090023 0.00386177 0.64321958 0.85480869 0.35848254 0.57825701
#> [91] 0.48892287 0.89640581 0.47771819 0.68545861 0.42249367 0.85480869
#> [97] 0.52281591 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 187 155 81 158 157 111 36 183 128 149 108 190 140
#> 9.92 13.08 14.06 20.14 15.10 17.45 21.19 9.24 20.35 8.37 18.29 20.81 12.68
#> 8 36.1 180 13 29 91 128.1 96 51 30 167 108.1 145
#> 18.43 21.19 14.82 14.34 15.45 5.33 20.35 14.54 18.23 17.43 15.55 18.29 10.07
#> 60 10 190.1 36.2 69 106 128.2 111.1 155.1 63 45 154 29.1
#> 13.15 10.53 20.81 21.19 23.23 16.67 20.35 17.45 13.08 22.77 17.42 12.63 15.45
#> 175 167.1 18 159 6 15 23 170 100 167.2 150 69.1 140.1
#> 21.91 15.55 15.21 10.55 15.64 22.68 16.92 19.54 16.07 15.55 20.33 23.23 12.68
#> 164 79 58 181 164.1 92 68 177 155.2 15.1 179 158.1 107
#> 23.60 16.23 19.34 16.46 23.60 22.92 20.62 12.53 13.08 22.68 18.63 20.14 11.18
#> 45.1 140.2 51.1 179.1 51.2 113 60.1 85 16 107.1 96.1 134 58.1
#> 17.42 12.68 18.23 18.63 18.23 22.86 13.15 16.44 8.71 11.18 14.54 17.81 19.34
#> 8.1 57 70 88 100.1 166 30.1 164.2 18.1 43 134.1 39 181.1
#> 18.43 14.46 7.38 18.37 16.07 19.98 17.43 23.60 15.21 12.10 17.81 15.59 16.46
#> 159.1 171 133 45.2 43.1 79.1 46 182 28 12 35 182.1 95
#> 10.55 16.57 14.65 17.42 12.10 16.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 2 80 198 27 28.1 126 162 122 161 7 148 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 104 151 7.1 196 34 120 126.1 72 95.1 144 64.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 87 198.1 138 198.2 74 11 75 47 21 174 102 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.2 31 152 74.1 182.2 7.2 102.1 120.1 126.2 75.1 87.1 20 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 135 27.1 178 71 64.2 67 116 165 98 48 122.1 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 196.1 162.1 118 19 87.2 147 44.1 109 116.1 82 174.1 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 141 198.3
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[8]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01450895 0.63820481 0.56474755
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.41287894 0.01893673 0.94558702
#> grade_iii, Cure model
#> 1.27449470
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 159 10.55 1 50 0 1
#> 58.1 19.34 1 39 0 0
#> 55 19.34 1 69 0 1
#> 128 20.35 1 35 0 1
#> 43 12.10 1 61 0 1
#> 158 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 123 13.00 1 44 1 0
#> 89 11.44 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 154 12.63 1 20 1 0
#> 170 19.54 1 43 0 1
#> 139 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 190 20.81 1 42 1 0
#> 56 12.21 1 60 0 0
#> 37 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 24 23.89 1 38 0 0
#> 58.2 19.34 1 39 0 0
#> 25 6.32 1 34 1 0
#> 97 19.14 1 65 0 1
#> 149 8.37 1 33 1 0
#> 39 15.59 1 37 0 1
#> 91 5.33 1 61 0 1
#> 42 12.43 1 49 0 1
#> 57 14.46 1 45 0 1
#> 76 19.22 1 54 0 1
#> 125 15.65 1 67 1 0
#> 169 22.41 1 46 0 0
#> 97.1 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 133 14.65 1 57 0 0
#> 123.1 13.00 1 44 1 0
#> 60 13.15 1 38 1 0
#> 66.1 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 13 14.34 1 54 0 1
#> 140 12.68 1 59 1 0
#> 39.1 15.59 1 37 0 1
#> 195 11.76 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 100 16.07 1 60 0 0
#> 197 21.60 1 69 1 0
#> 42.1 12.43 1 49 0 1
#> 99 21.19 1 38 0 1
#> 150 20.33 1 48 0 0
#> 194 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 36 21.19 1 48 0 1
#> 96 14.54 1 33 0 1
#> 145 10.07 1 65 1 0
#> 170.1 19.54 1 43 0 1
#> 29.1 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 106.1 16.67 1 49 1 0
#> 36.1 21.19 1 48 0 1
#> 136 21.83 1 43 0 1
#> 39.2 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 150.1 20.33 1 48 0 0
#> 133.1 14.65 1 57 0 0
#> 171.1 16.57 1 41 0 1
#> 39.3 15.59 1 37 0 1
#> 51 18.23 1 83 0 1
#> 194.1 22.40 1 38 0 1
#> 58.3 19.34 1 39 0 0
#> 30 17.43 1 78 0 0
#> 189.1 10.51 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 66.2 22.13 1 53 0 0
#> 16 8.71 1 71 0 1
#> 124 9.73 1 NA 1 0
#> 171.2 16.57 1 41 0 1
#> 100.1 16.07 1 60 0 0
#> 69 23.23 1 25 0 1
#> 170.2 19.54 1 43 0 1
#> 16.1 8.71 1 71 0 1
#> 158.1 20.14 1 74 1 0
#> 77 7.27 1 67 0 1
#> 145.1 10.07 1 65 1 0
#> 175 21.91 1 43 0 0
#> 195.1 11.76 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 57.1 14.46 1 45 0 1
#> 89.1 11.44 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 43.1 12.10 1 61 0 1
#> 8.1 18.43 1 32 0 0
#> 97.2 19.14 1 65 0 1
#> 134 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 134.1 17.81 1 47 1 0
#> 166 19.98 1 48 0 0
#> 91.1 5.33 1 61 0 1
#> 149.1 8.37 1 33 1 0
#> 134.2 17.81 1 47 1 0
#> 39.4 15.59 1 37 0 1
#> 96.1 14.54 1 33 0 1
#> 49.1 12.19 1 48 1 0
#> 63 22.77 1 31 1 0
#> 153 21.33 1 55 1 0
#> 96.2 14.54 1 33 0 1
#> 101 9.97 1 10 0 1
#> 128.1 20.35 1 35 0 1
#> 107 11.18 1 54 1 0
#> 8.2 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 90.1 20.94 1 50 0 1
#> 191 24.00 0 60 0 1
#> 53 24.00 0 32 0 1
#> 112 24.00 0 61 0 0
#> 182 24.00 0 35 0 0
#> 7 24.00 0 37 1 0
#> 147 24.00 0 76 1 0
#> 182.1 24.00 0 35 0 0
#> 131 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 75 24.00 0 21 1 0
#> 21 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 186 24.00 0 45 1 0
#> 131.1 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 138.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 67.1 24.00 0 25 0 0
#> 141 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 115.1 24.00 0 NA 1 0
#> 72 24.00 0 40 0 1
#> 17 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 72.1 24.00 0 40 0 1
#> 31.1 24.00 0 36 0 1
#> 75.1 24.00 0 21 1 0
#> 102 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 142 24.00 0 53 0 0
#> 141.1 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 38.1 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 102.1 24.00 0 49 0 0
#> 126 24.00 0 48 0 0
#> 38.2 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 163.1 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 186.1 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 17.1 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 109.1 24.00 0 48 0 0
#> 131.2 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 17.2 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 142.1 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 31.2 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 120 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 151.2 24.00 0 42 0 0
#> 72.2 24.00 0 40 0 1
#> 62 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 172.1 24.00 0 41 0 0
#> 131.3 24.00 0 66 0 0
#> 182.2 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.41 NA NA NA
#> 2 age, Cure model 0.0189 NA NA NA
#> 3 grade_ii, Cure model 0.946 NA NA NA
#> 4 grade_iii, Cure model 1.27 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0145 NA NA NA
#> 2 grade_ii, Survival model 0.638 NA NA NA
#> 3 grade_iii, Survival model 0.565 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.41288 0.01894 0.94559 1.27449
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 246.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.41287894 0.01893673 0.94558702 1.27449470
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01450895 0.63820481 0.56474755
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6921196 0.9611269 0.6921196 0.6921196 0.6152139 0.9514583 0.6491380
#> [8] 0.8152640 0.9643029 0.9170796 0.5769982 0.9277296 0.6715663 0.5187717
#> [15] 0.8714342 0.6060623 0.9414691 0.9312325 0.4111484 0.1116581 0.6921196
#> [22] 0.9914158 0.7361720 0.9826065 0.8511291 0.9943160 0.9346921 0.9023339
#> [29] 0.7239076 0.8468202 0.3330699 0.7361720 0.7586397 0.8832429 0.9170796
#> [36] 0.9134360 0.4111484 0.9448469 0.9097588 0.9242064 0.8511291 0.7239076
#> [43] 0.8335282 0.5036030 0.9346921 0.5450909 0.6324048 0.3653236 0.8057265
#> [50] 0.5450909 0.8909981 0.9674504 0.6715663 0.8714342 0.7530176 0.8057265
#> [57] 0.5450909 0.4862666 0.8511291 0.7805276 0.6324048 0.8832429 0.8152640
#> [64] 0.8511291 0.7751660 0.3653236 0.6921196 0.8007758 0.8424217 0.4111484
#> [71] 0.9766419 0.8152640 0.8335282 0.1986647 0.6715663 0.9766419 0.6491380
#> [78] 0.9884976 0.9674504 0.4673948 0.8793123 0.9023339 0.2511769 0.9514583
#> [85] 0.7586397 0.7361720 0.7858223 0.8290023 0.7858223 0.6641184 0.9943160
#> [92] 0.9826065 0.7858223 0.8511291 0.8909981 0.9448469 0.2975579 0.5324516
#> [99] 0.8909981 0.9735815 0.6152139 0.9579231 0.7586397 0.5965544 0.5769982
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000
#>
#> $Time
#> 58 159 58.1 55 128 43 158 171 93 123 90 154 170
#> 19.34 10.55 19.34 19.34 20.35 12.10 20.14 16.57 10.33 13.00 20.94 12.63 19.54
#> 139 29 190 56 37 66 24 58.2 25 97 149 39 91
#> 21.49 15.45 20.81 12.21 12.52 22.13 23.89 19.34 6.32 19.14 8.37 15.59 5.33
#> 42 57 76 125 169 97.1 8 133 123.1 60 66.1 49 13
#> 12.43 14.46 19.22 15.65 22.41 19.14 18.43 14.65 13.00 13.15 22.13 12.19 14.34
#> 140 39.1 76.1 100 197 42.1 99 150 194 106 36 96 145
#> 12.68 15.59 19.22 16.07 21.60 12.43 21.19 20.33 22.40 16.67 21.19 14.54 10.07
#> 170.1 29.1 179 106.1 36.1 136 39.2 40 150.1 133.1 171.1 39.3 51
#> 19.54 15.45 18.63 16.67 21.19 21.83 15.59 18.00 20.33 14.65 16.57 15.59 18.23
#> 194.1 58.3 30 26 66.2 16 171.2 100.1 69 170.2 16.1 158.1 77
#> 22.40 19.34 17.43 15.77 22.13 8.71 16.57 16.07 23.23 19.54 8.71 20.14 7.27
#> 145.1 175 157 57.1 113 43.1 8.1 97.2 134 79 134.1 166 91.1
#> 10.07 21.91 15.10 14.46 22.86 12.10 18.43 19.14 17.81 16.23 17.81 19.98 5.33
#> 149.1 134.2 39.4 96.1 49.1 63 153 96.2 101 128.1 107 8.2 32
#> 8.37 17.81 15.59 14.54 12.19 22.77 21.33 14.54 9.97 20.35 11.18 18.43 20.90
#> 90.1 191 53 112 182 7 147 182.1 131 138 67 75 21
#> 20.94 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 186 131.1 2 138.1 31 67.1 141 38 9 193 35 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 17 172 83 47 163 72.1 31.1 75.1 102 109 185 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 142 141.1 11 80 176 151 38.1 116 122 151.1 161 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 126 38.2 46 27 163.1 54 186.1 71 17.1 144 109.1 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 17.2 146 95 104 142.1 132 44 31.2 65 33 162 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 84 151.2 72.2 62 165 172.1 131.3 182.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[9]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01271064 0.90021420 0.35526974
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.419749269 -0.011532172 0.009056175
#> grade_iii, Cure model
#> 0.984460706
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 117 17.46 1 26 0 1
#> 194 22.40 1 38 0 1
#> 184 17.77 1 38 0 0
#> 96 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 171 16.57 1 41 0 1
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 92 22.92 1 47 0 1
#> 42 12.43 1 49 0 1
#> 168 23.72 1 70 0 0
#> 45 17.42 1 54 0 1
#> 100 16.07 1 60 0 0
#> 78 23.88 1 43 0 0
#> 188 16.16 1 46 0 1
#> 134 17.81 1 47 1 0
#> 70 7.38 1 30 1 0
#> 189 10.51 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 93 10.33 1 52 0 1
#> 70.1 7.38 1 30 1 0
#> 133 14.65 1 57 0 0
#> 159 10.55 1 50 0 1
#> 187 9.92 1 39 1 0
#> 41 18.02 1 40 1 0
#> 93.1 10.33 1 52 0 1
#> 70.2 7.38 1 30 1 0
#> 26.1 15.77 1 49 0 1
#> 81 14.06 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 123 13.00 1 44 1 0
#> 76 19.22 1 54 0 1
#> 123.1 13.00 1 44 1 0
#> 25 6.32 1 34 1 0
#> 184.1 17.77 1 38 0 0
#> 179 18.63 1 42 0 0
#> 154 12.63 1 20 1 0
#> 155 13.08 1 26 0 0
#> 37 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 70.3 7.38 1 30 1 0
#> 145 10.07 1 65 1 0
#> 170 19.54 1 43 0 1
#> 55 19.34 1 69 0 1
#> 113 22.86 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 166 19.98 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 107 11.18 1 54 1 0
#> 154.1 12.63 1 20 1 0
#> 111 17.45 1 47 0 1
#> 96.1 14.54 1 33 0 1
#> 194.1 22.40 1 38 0 1
#> 76.1 19.22 1 54 0 1
#> 187.1 9.92 1 39 1 0
#> 39.1 15.59 1 37 0 1
#> 153 21.33 1 55 1 0
#> 187.2 9.92 1 39 1 0
#> 107.1 11.18 1 54 1 0
#> 6 15.64 1 39 0 0
#> 14 12.89 1 21 0 0
#> 169 22.41 1 46 0 0
#> 117.1 17.46 1 26 0 1
#> 15 22.68 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 85 16.44 1 36 0 0
#> 106.1 16.67 1 49 1 0
#> 159.1 10.55 1 50 0 1
#> 69 23.23 1 25 0 1
#> 4.1 17.64 1 NA 0 1
#> 197 21.60 1 69 1 0
#> 43 12.10 1 61 0 1
#> 111.1 17.45 1 47 0 1
#> 127 3.53 1 62 0 1
#> 133.1 14.65 1 57 0 0
#> 89.1 11.44 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 155.1 13.08 1 26 0 0
#> 16 8.71 1 71 0 1
#> 177 12.53 1 75 0 0
#> 96.2 14.54 1 33 0 1
#> 61 10.12 1 36 0 1
#> 133.2 14.65 1 57 0 0
#> 4.2 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 13 14.34 1 54 0 1
#> 175 21.91 1 43 0 0
#> 18 15.21 1 49 1 0
#> 117.2 17.46 1 26 0 1
#> 155.2 13.08 1 26 0 0
#> 153.1 21.33 1 55 1 0
#> 79 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 29.1 15.45 1 68 1 0
#> 108 18.29 1 39 0 1
#> 92.1 22.92 1 47 0 1
#> 41.1 18.02 1 40 1 0
#> 117.3 17.46 1 26 0 1
#> 136 21.83 1 43 0 1
#> 170.1 19.54 1 43 0 1
#> 57 14.46 1 45 0 1
#> 81.1 14.06 1 34 0 0
#> 14.1 12.89 1 21 0 0
#> 76.2 19.22 1 54 0 1
#> 179.1 18.63 1 42 0 0
#> 150.1 20.33 1 48 0 0
#> 167 15.55 1 56 1 0
#> 36 21.19 1 48 0 1
#> 102 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 103 24.00 0 56 1 0
#> 2 24.00 0 9 0 0
#> 44 24.00 0 56 0 0
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 95 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 80 24.00 0 41 0 0
#> 64.1 24.00 0 43 0 0
#> 120 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 120.1 24.00 0 68 0 1
#> 102.1 24.00 0 49 0 0
#> 20 24.00 0 46 1 0
#> 34 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 115 24.00 0 NA 1 0
#> 54 24.00 0 53 1 0
#> 3 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 200.1 24.00 0 64 0 0
#> 162.1 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 7.1 24.00 0 37 1 0
#> 1.1 24.00 0 23 1 0
#> 120.2 24.00 0 68 0 1
#> 115.1 24.00 0 NA 1 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 31 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 115.2 24.00 0 NA 1 0
#> 141 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 200.2 24.00 0 64 0 0
#> 131 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 162.2 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 120.3 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 54.1 24.00 0 53 1 0
#> 121 24.00 0 57 1 0
#> 120.4 24.00 0 68 0 1
#> 48 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 196 24.00 0 19 0 0
#> 178 24.00 0 52 1 0
#> 104.1 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 83.1 24.00 0 6 0 0
#> 1.2 24.00 0 23 1 0
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 64.2 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 174.1 24.00 0 49 1 0
#> 74 24.00 0 43 0 1
#> 131.1 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 173 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 141.1 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 17 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 121.1 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 75 24.00 0 21 1 0
#> 191.1 24.00 0 60 0 1
#> 131.2 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 31.1 24.00 0 36 0 1
#> 75.1 24.00 0 21 1 0
#> 44.1 24.00 0 56 0 0
#> 160 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.420 NA NA NA
#> 2 age, Cure model -0.0115 NA NA NA
#> 3 grade_ii, Cure model 0.00906 NA NA NA
#> 4 grade_iii, Cure model 0.984 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0127 NA NA NA
#> 2 grade_ii, Survival model 0.900 NA NA NA
#> 3 grade_iii, Survival model 0.355 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.419749 -0.011532 0.009056 0.984461
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 248.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.419749269 -0.011532172 0.009056175 0.984460706
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01271064 0.90021420 0.35526974
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2931029347 0.0603502122 0.2735710587 0.5637329754 0.5017541646
#> [6] 0.3798953273 0.1328539283 0.4400505808 0.0266388672 0.7667969652
#> [11] 0.0077985590 0.3503903005 0.4298732222 0.0033794910 0.4198228284
#> [16] 0.2638941265 0.9382879593 0.4707626355 0.8524164919 0.9382879593
#> [21] 0.5325453448 0.8201816297 0.8958423437 0.2446503142 0.8524164919
#> [26] 0.9382879593 0.4400505808 0.6163965505 0.3604324135 0.6703179800
#> [31] 0.1865201481 0.6703179800 0.9792716314 0.2735710587 0.2145712813
#> [36] 0.7243908539 0.6378913510 0.7561327611 0.1244924207 0.9382879593
#> [41] 0.8849531083 0.1590886543 0.1770822051 0.0384003998 0.0006681704
#> [46] 0.1500072699 0.7667969652 0.7988979393 0.7243908539 0.3307502590
#> [51] 0.5637329754 0.0603502122 0.1865201481 0.8958423437 0.4707626355
#> [56] 0.1006355482 0.8958423437 0.7988979393 0.4603883267 0.6918297882
#> [61] 0.0525431718 0.2931029347 0.0452189744 0.0145321157 0.3997617088
#> [66] 0.3604324135 0.8201816297 0.0206125971 0.0921890368 0.7881153212
#> [71] 0.3307502590 0.9896167496 0.5325453448 0.8416011986 0.6378913510
#> [76] 0.9275453671 0.7454395905 0.5637329754 0.8740535703 0.5325453448
#> [81] 0.3897940013 0.6056860401 0.0754077330 0.5222566613 0.2931029347
#> [86] 0.6378913510 0.1006355482 0.4098215275 0.7134994881 0.5017541646
#> [91] 0.2344387117 0.0266388672 0.2446503142 0.2931029347 0.0837248978
#> [96] 0.1590886543 0.5950286538 0.6163965505 0.6918297882 0.1865201481
#> [101] 0.2145712813 0.1328539283 0.4913804086 0.1162661112 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 117 194 184 96 29 171 150 26 92 42 168 45 100
#> 17.46 22.40 17.77 14.54 15.45 16.57 20.33 15.77 22.92 12.43 23.72 17.42 16.07
#> 78 188 134 70 39 93 70.1 133 159 187 41 93.1 70.2
#> 23.88 16.16 17.81 7.38 15.59 10.33 7.38 14.65 10.55 9.92 18.02 10.33 7.38
#> 26.1 81 106 123 76 123.1 25 184.1 179 154 155 37 90
#> 15.77 14.06 16.67 13.00 19.22 13.00 6.32 17.77 18.63 12.63 13.08 12.52 20.94
#> 70.3 145 170 55 113 24 166 42.1 107 154.1 111 96.1 194.1
#> 7.38 10.07 19.54 19.34 22.86 23.89 19.98 12.43 11.18 12.63 17.45 14.54 22.40
#> 76.1 187.1 39.1 153 187.2 107.1 6 14 169 117.1 15 129 85
#> 19.22 9.92 15.59 21.33 9.92 11.18 15.64 12.89 22.41 17.46 22.68 23.41 16.44
#> 106.1 159.1 69 197 43 111.1 127 133.1 52 155.1 16 177 96.2
#> 16.67 10.55 23.23 21.60 12.10 17.45 3.53 14.65 10.42 13.08 8.71 12.53 14.54
#> 61 133.2 130 13 175 18 117.2 155.2 153.1 79 140 29.1 108
#> 10.12 14.65 16.47 14.34 21.91 15.21 17.46 13.08 21.33 16.23 12.68 15.45 18.29
#> 92.1 41.1 117.3 136 170.1 57 81.1 14.1 76.2 179.1 150.1 167 36
#> 22.92 18.02 17.46 21.83 19.54 14.46 14.06 12.89 19.22 18.63 20.33 15.55 21.19
#> 102 1 103 2 44 94 47 64 95 151 80 64.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 12 112 120.1 102.1 20 34 65 148 54 3 7 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 200.1 162.1 47.1 7.1 1.1 120.2 9 31 193 141 103.1 200.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 122 162.2 174 120.3 186 191 54.1 121 120.4 48 28 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 104.1 83 83.1 1.2 109 152 64.2 126 174.1 74 131.1 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 142 137 141.1 137.1 172 132 17 186.1 121.1 84 75 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.2 178.1 31.1 75.1 44.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[10]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 6.680824e-05 3.240023e-01 5.787409e-01
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.60362364 0.01500539 -0.20753614
#> grade_iii, Cure model
#> 0.64038247
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 37 12.52 1 57 1 0
#> 194 22.40 1 38 0 1
#> 88 18.37 1 47 0 0
#> 63 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 117 17.46 1 26 0 1
#> 187 9.92 1 39 1 0
#> 10 10.53 1 34 0 0
#> 188 16.16 1 46 0 1
#> 51 18.23 1 83 0 1
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 85 16.44 1 36 0 0
#> 177 12.53 1 75 0 0
#> 88.1 18.37 1 47 0 0
#> 100 16.07 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 39 15.59 1 37 0 1
#> 179 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 184.1 17.77 1 38 0 0
#> 171 16.57 1 41 0 1
#> 159 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 5 16.43 1 51 0 1
#> 5.1 16.43 1 51 0 1
#> 158 20.14 1 74 1 0
#> 134 17.81 1 47 1 0
#> 100.1 16.07 1 60 0 0
#> 24.1 23.89 1 38 0 0
#> 77.1 7.27 1 67 0 1
#> 37.1 12.52 1 57 1 0
#> 189 10.51 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 197 21.60 1 69 1 0
#> 8 18.43 1 32 0 0
#> 15 22.68 1 48 0 0
#> 175 21.91 1 43 0 0
#> 168 23.72 1 70 0 0
#> 43 12.10 1 61 0 1
#> 85.1 16.44 1 36 0 0
#> 66 22.13 1 53 0 0
#> 15.1 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 127.1 3.53 1 62 0 1
#> 26 15.77 1 49 0 1
#> 52 10.42 1 52 0 1
#> 93 10.33 1 52 0 1
#> 88.2 18.37 1 47 0 0
#> 6 15.64 1 39 0 0
#> 63.1 22.77 1 31 1 0
#> 85.2 16.44 1 36 0 0
#> 181 16.46 1 45 0 1
#> 117.1 17.46 1 26 0 1
#> 184.2 17.77 1 38 0 0
#> 175.1 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 41.1 18.02 1 40 1 0
#> 149 8.37 1 33 1 0
#> 26.1 15.77 1 49 0 1
#> 150.1 20.33 1 48 0 0
#> 175.2 21.91 1 43 0 0
#> 129 23.41 1 53 1 0
#> 36 21.19 1 48 0 1
#> 49 12.19 1 48 1 0
#> 39.1 15.59 1 37 0 1
#> 145 10.07 1 65 1 0
#> 197.1 21.60 1 69 1 0
#> 197.2 21.60 1 69 1 0
#> 154.1 12.63 1 20 1 0
#> 167 15.55 1 56 1 0
#> 86 23.81 1 58 0 1
#> 194.1 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 51.1 18.23 1 83 0 1
#> 50 10.02 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 77.2 7.27 1 67 0 1
#> 91 5.33 1 61 0 1
#> 136 21.83 1 43 0 1
#> 171.1 16.57 1 41 0 1
#> 129.1 23.41 1 53 1 0
#> 197.3 21.60 1 69 1 0
#> 188.1 16.16 1 46 0 1
#> 129.2 23.41 1 53 1 0
#> 66.1 22.13 1 53 0 0
#> 111 17.45 1 47 0 1
#> 164 23.60 1 76 0 1
#> 139 21.49 1 63 1 0
#> 145.1 10.07 1 65 1 0
#> 56 12.21 1 60 0 0
#> 92 22.92 1 47 0 1
#> 60 13.15 1 38 1 0
#> 183 9.24 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 190.1 20.81 1 42 1 0
#> 30 17.43 1 78 0 0
#> 124 9.73 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 8.1 18.43 1 32 0 0
#> 30.1 17.43 1 78 0 0
#> 189.1 10.51 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 56.1 12.21 1 60 0 0
#> 51.2 18.23 1 83 0 1
#> 5.2 16.43 1 51 0 1
#> 152 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 182 24.00 0 35 0 0
#> 143 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 185 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#> 132 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 28 24.00 0 67 1 0
#> 31 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 33 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 178 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#> 165.1 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 174.1 24.00 0 49 1 0
#> 156 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 9 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 74 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 9.1 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 75 24.00 0 21 1 0
#> 122.1 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 82.1 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 72 24.00 0 40 0 1
#> 131 24.00 0 66 0 0
#> 152.1 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 156.1 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 33.1 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 102.1 24.00 0 49 0 0
#> 33.2 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 73.1 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 22 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 73.2 24.00 0 NA 0 1
#> 48 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 162 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 163.1 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 75.1 24.00 0 21 1 0
#> 67 24.00 0 25 0 0
#> 22.1 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 193.1 24.00 0 45 0 1
#> 102.2 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 98 24.00 0 34 1 0
#> 131.1 24.00 0 66 0 0
#> 7.2 24.00 0 37 1 0
#> 84 24.00 0 39 0 1
#> 103.1 24.00 0 56 1 0
#> 38.1 24.00 0 31 1 0
#> 104.1 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.604 NA NA NA
#> 2 age, Cure model 0.0150 NA NA NA
#> 3 grade_ii, Cure model -0.208 NA NA NA
#> 4 grade_iii, Cure model 0.640 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0000668 NA NA NA
#> 2 grade_ii, Survival model 0.324 NA NA NA
#> 3 grade_iii, Survival model 0.579 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.60362 0.01501 -0.20754 0.64038
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 255.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.60362364 0.01500539 -0.20753614 0.64038247
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 6.680824e-05 3.240023e-01 5.787409e-01
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.05606912 0.84029323 0.22860852 0.45038832 0.18133044 0.73665082
#> [7] 0.56698233 0.92556155 0.89049107 0.69039482 0.47845465 0.95321325
#> [13] 0.02067904 0.54084296 0.64263457 0.83302550 0.45038832 0.70590063
#> [19] 0.78171932 0.75937510 0.42191026 0.79657103 0.81123421 0.54084296
#> [25] 0.60961232 0.88338825 0.81855280 0.66685228 0.66685228 0.41234577
#> [31] 0.53198455 0.70590063 0.02067904 0.95321325 0.84029323 0.50527310
#> [37] 0.31521583 0.43147416 0.20497233 0.27231893 0.09629603 0.87624003
#> [43] 0.64263457 0.25046650 0.20497233 0.98678301 0.98678301 0.72140508
#> [49] 0.89759376 0.90465233 0.45038832 0.75177486 0.18133044 0.64263457
#> [55] 0.63445770 0.56698233 0.54084296 0.27231893 0.39326832 0.50527310
#> [61] 0.94633998 0.72140508 0.39326832 0.27231893 0.13050155 0.36432634
#> [67] 0.86904539 0.75937510 0.91166766 0.31521583 0.31521583 0.81855280
#> [73] 0.77426577 0.07818176 0.22860852 0.37418808 0.47845465 0.97334248
#> [79] 0.95321325 0.98008097 0.30442445 0.60961232 0.13050155 0.31521583
#> [85] 0.69039482 0.13050155 0.25046650 0.58412745 0.11440456 0.35424928
#> [91] 0.91166766 0.85466979 0.16842845 0.80391553 0.93251453 0.73665082
#> [97] 0.37418808 0.59266423 0.93944740 0.43147416 0.59266423 0.78917270
#> [103] 0.52306869 0.62619682 0.85466979 0.47845465 0.66685228 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 78 37 194 88 63 125 117 187 10 188 51 77 24
#> 23.88 12.52 22.40 18.37 22.77 15.65 17.46 9.92 10.53 16.16 18.23 7.27 23.89
#> 184 85 177 88.1 100 180 39 179 57 14 184.1 171 159
#> 17.77 16.44 12.53 18.37 16.07 14.82 15.59 18.63 14.46 12.89 17.77 16.57 10.55
#> 154 5 5.1 158 134 100.1 24.1 77.1 37.1 41 197 8 15
#> 12.63 16.43 16.43 20.14 17.81 16.07 23.89 7.27 12.52 18.02 21.60 18.43 22.68
#> 175 168 43 85.1 66 15.1 127 127.1 26 52 93 88.2 6
#> 21.91 23.72 12.10 16.44 22.13 22.68 3.53 3.53 15.77 10.42 10.33 18.37 15.64
#> 63.1 85.2 181 117.1 184.2 175.1 150 41.1 149 26.1 150.1 175.2 129
#> 22.77 16.44 16.46 17.46 17.77 21.91 20.33 18.02 8.37 15.77 20.33 21.91 23.41
#> 36 49 39.1 145 197.1 197.2 154.1 167 86 194.1 190 51.1 25
#> 21.19 12.19 15.59 10.07 21.60 21.60 12.63 15.55 23.81 22.40 20.81 18.23 6.32
#> 77.2 91 136 171.1 129.1 197.3 188.1 129.2 66.1 111 164 139 145.1
#> 7.27 5.33 21.83 16.57 23.41 21.60 16.16 23.41 22.13 17.45 23.60 21.49 10.07
#> 56 92 60 183 125.1 190.1 30 16 8.1 30.1 96 40 130
#> 12.21 22.92 13.15 9.24 15.65 20.81 17.43 8.71 18.43 17.43 14.54 18.00 16.47
#> 56.1 51.2 5.2 152 151 182 143 94 185 82 174 132 137
#> 12.21 18.23 16.43 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 17 7 28 31 104 33 163 121 87 178 141 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 21 165.1 47 62 174.1 156 193 147 102 9 116 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 198 74 135 9.1 27.1 75 122.1 126 82.1 144 72 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 178.1 156.1 19 38 7.1 33.1 138 102.1 33.2 72.1 2 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 48 19.1 162 80 163.1 138.1 142.1 75.1 67 22.1 103 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.2 46 53 98 131.1 7.2 84 103.1 38.1 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[11]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008125443 1.480114032 0.807379074
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.547552155 0.005292691 0.396798799
#> grade_iii, Cure model
#> 1.064209603
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 50 10.02 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 70 7.38 1 30 1 0
#> 36 21.19 1 48 0 1
#> 45.1 17.42 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 133 14.65 1 57 0 0
#> 40 18.00 1 28 1 0
#> 105 19.75 1 60 0 0
#> 90 20.94 1 50 0 1
#> 97 19.14 1 65 0 1
#> 30 17.43 1 78 0 0
#> 101 9.97 1 10 0 1
#> 18 15.21 1 49 1 0
#> 113 22.86 1 34 0 0
#> 105.1 19.75 1 60 0 0
#> 123 13.00 1 44 1 0
#> 159 10.55 1 50 0 1
#> 150 20.33 1 48 0 0
#> 88 18.37 1 47 0 0
#> 29 15.45 1 68 1 0
#> 60.1 13.15 1 38 1 0
#> 88.1 18.37 1 47 0 0
#> 154 12.63 1 20 1 0
#> 181 16.46 1 45 0 1
#> 60.2 13.15 1 38 1 0
#> 111 17.45 1 47 0 1
#> 55 19.34 1 69 0 1
#> 175 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 36.1 21.19 1 48 0 1
#> 111.1 17.45 1 47 0 1
#> 26 15.77 1 49 0 1
#> 8 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 32 20.90 1 37 1 0
#> 50.1 10.02 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 159.1 10.55 1 50 0 1
#> 145 10.07 1 65 1 0
#> 76 19.22 1 54 0 1
#> 45.2 17.42 1 54 0 1
#> 134 17.81 1 47 1 0
#> 69 23.23 1 25 0 1
#> 140 12.68 1 59 1 0
#> 194 22.40 1 38 0 1
#> 100 16.07 1 60 0 0
#> 106 16.67 1 49 1 0
#> 145.1 10.07 1 65 1 0
#> 37 12.52 1 57 1 0
#> 134.1 17.81 1 47 1 0
#> 42 12.43 1 49 0 1
#> 181.1 16.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 8.1 18.43 1 32 0 0
#> 110 17.56 1 65 0 1
#> 145.2 10.07 1 65 1 0
#> 97.1 19.14 1 65 0 1
#> 49 12.19 1 48 1 0
#> 66 22.13 1 53 0 0
#> 183 9.24 1 67 1 0
#> 127.1 3.53 1 62 0 1
#> 4 17.64 1 NA 0 1
#> 134.2 17.81 1 47 1 0
#> 39 15.59 1 37 0 1
#> 167 15.55 1 56 1 0
#> 136 21.83 1 43 0 1
#> 66.1 22.13 1 53 0 0
#> 105.2 19.75 1 60 0 0
#> 158 20.14 1 74 1 0
#> 192 16.44 1 31 1 0
#> 171 16.57 1 41 0 1
#> 150.1 20.33 1 48 0 0
#> 52 10.42 1 52 0 1
#> 25 6.32 1 34 1 0
#> 36.2 21.19 1 48 0 1
#> 29.1 15.45 1 68 1 0
#> 199 19.81 1 NA 0 1
#> 42.1 12.43 1 49 0 1
#> 99 21.19 1 38 0 1
#> 188 16.16 1 46 0 1
#> 113.1 22.86 1 34 0 0
#> 23 16.92 1 61 0 0
#> 88.2 18.37 1 47 0 0
#> 189.1 10.51 1 NA 1 0
#> 192.1 16.44 1 31 1 0
#> 42.2 12.43 1 49 0 1
#> 70.1 7.38 1 30 1 0
#> 96 14.54 1 33 0 1
#> 49.1 12.19 1 48 1 0
#> 15 22.68 1 48 0 0
#> 18.1 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 110.1 17.56 1 65 0 1
#> 190 20.81 1 42 1 0
#> 187 9.92 1 39 1 0
#> 195 11.76 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 125.1 15.65 1 67 1 0
#> 177 12.53 1 75 0 0
#> 49.2 12.19 1 48 1 0
#> 88.3 18.37 1 47 0 0
#> 189.2 10.51 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 29.2 15.45 1 68 1 0
#> 37.1 12.52 1 57 1 0
#> 26.1 15.77 1 49 0 1
#> 158.1 20.14 1 74 1 0
#> 106.1 16.67 1 49 1 0
#> 52.1 10.42 1 52 0 1
#> 146 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 147 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 28 24.00 0 67 1 0
#> 22 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 163 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 122.1 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 22.1 24.00 0 52 1 0
#> 22.2 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 38 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 162 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 19 24.00 0 57 0 1
#> 161 24.00 0 45 0 0
#> 71 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 186 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 160.1 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 141.1 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 147.1 24.00 0 76 1 0
#> 191 24.00 0 60 0 1
#> 44 24.00 0 56 0 0
#> 198 24.00 0 66 0 1
#> 132 24.00 0 55 0 0
#> 119.1 24.00 0 17 0 0
#> 182 24.00 0 35 0 0
#> 132.1 24.00 0 55 0 0
#> 116 24.00 0 58 0 1
#> 116.1 24.00 0 58 0 1
#> 95.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 161.1 24.00 0 45 0 0
#> 144 24.00 0 28 0 1
#> 27 24.00 0 63 1 0
#> 163.1 24.00 0 66 0 0
#> 119.2 24.00 0 17 0 0
#> 144.1 24.00 0 28 0 1
#> 120 24.00 0 68 0 1
#> 28.1 24.00 0 67 1 0
#> 53 24.00 0 32 0 1
#> 27.1 24.00 0 63 1 0
#> 84.1 24.00 0 39 0 1
#> 122.2 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 131 24.00 0 66 0 0
#> 163.2 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 142.2 24.00 0 53 0 0
#> 147.2 24.00 0 76 1 0
#> 84.2 24.00 0 39 0 1
#> 173 24.00 0 19 0 1
#> 115 24.00 0 NA 1 0
#> 104 24.00 0 50 1 0
#> 186.1 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 112 24.00 0 61 0 0
#> 46 24.00 0 71 0 0
#> 160.2 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 122.3 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 185 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 160.3 24.00 0 31 1 0
#> 163.3 24.00 0 66 0 0
#> 191.1 24.00 0 60 0 1
#> 122.4 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 48 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.548 NA NA NA
#> 2 age, Cure model 0.00529 NA NA NA
#> 3 grade_ii, Cure model 0.397 NA NA NA
#> 4 grade_iii, Cure model 1.06 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00813 NA NA NA
#> 2 grade_ii, Survival model 1.48 NA NA NA
#> 3 grade_iii, Survival model 0.807 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.547552 0.005293 0.396799 1.064210
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 255.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.547552155 0.005292691 0.396798799 1.064209603
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008125443 1.480114032 0.807379074
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79994423 0.85460444 0.98834312 0.48371809 0.79994423 0.91605323
#> [7] 0.90929815 0.73970270 0.63663687 0.54456461 0.67952471 0.79431704
#> [13] 0.98098972 0.90251670 0.25557824 0.63663687 0.92559074 0.96027929
#> [19] 0.59596976 0.71011949 0.89192335 0.91605323 0.71011949 0.93179384
#> [25] 0.83601484 0.91605323 0.78303205 0.66278203 0.43551038 0.99539466
#> [31] 0.48371809 0.78303205 0.86770384 0.69487209 0.77717554 0.55943216
#> [37] 0.87616564 0.96027929 0.97352629 0.67128263 0.79994423 0.74688292
#> [43] 0.21592530 0.92872386 0.35656522 0.86336335 0.82120478 0.97352629
#> [49] 0.93784241 0.74688292 0.94364967 0.83601484 0.15773143 0.69487209
#> [55] 0.76534957 0.97352629 0.67952471 0.95216365 0.38485468 0.98592871
#> [61] 0.99539466 0.74688292 0.88412239 0.88807361 0.46098291 0.38485468
#> [67] 0.63663687 0.61861718 0.84554714 0.83110985 0.59596976 0.96562600
#> [73] 0.99306000 0.48371809 0.89192335 0.94364967 0.48371809 0.85900910
#> [79] 0.25557824 0.81588021 0.71011949 0.84554714 0.94364967 0.98834312
#> [85] 0.91268776 0.95216365 0.32277730 0.90251670 0.58432327 0.76534957
#> [91] 0.57257617 0.98347481 0.07792748 0.87616564 0.93482223 0.95216365
#> [97] 0.71011949 0.97090199 0.89192335 0.93784241 0.86770384 0.61861718
#> [103] 0.82120478 0.96562600 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 45 79 70 36 45.1 60 133 40 105 90 97 30 101
#> 17.42 16.23 7.38 21.19 17.42 13.15 14.65 18.00 19.75 20.94 19.14 17.43 9.97
#> 18 113 105.1 123 159 150 88 29 60.1 88.1 154 181 60.2
#> 15.21 22.86 19.75 13.00 10.55 20.33 18.37 15.45 13.15 18.37 12.63 16.46 13.15
#> 111 55 175 127 36.1 111.1 26 8 117 32 125 159.1 145
#> 17.45 19.34 21.91 3.53 21.19 17.45 15.77 18.43 17.46 20.90 15.65 10.55 10.07
#> 76 45.2 134 69 140 194 100 106 145.1 37 134.1 42 181.1
#> 19.22 17.42 17.81 23.23 12.68 22.40 16.07 16.67 10.07 12.52 17.81 12.43 16.46
#> 168 8.1 110 145.2 97.1 49 66 183 127.1 134.2 39 167 136
#> 23.72 18.43 17.56 10.07 19.14 12.19 22.13 9.24 3.53 17.81 15.59 15.55 21.83
#> 66.1 105.2 158 192 171 150.1 52 25 36.2 29.1 42.1 99 188
#> 22.13 19.75 20.14 16.44 16.57 20.33 10.42 6.32 21.19 15.45 12.43 21.19 16.16
#> 113.1 23 88.2 192.1 42.2 70.1 96 49.1 15 18.1 68 110.1 190
#> 22.86 16.92 18.37 16.44 12.43 7.38 14.54 12.19 22.68 15.21 20.62 17.56 20.81
#> 187 78 125.1 177 49.2 88.3 93 29.2 37.1 26.1 158.1 106.1 52.1
#> 9.92 23.88 15.65 12.53 12.19 18.37 10.33 15.45 12.52 15.77 20.14 16.67 10.42
#> 146 174 147 160 75 28 22 2 163 122 21 95 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 22.1 22.2 9 135 38 119 162 84 19 161 71 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 137 200 186 141 160.1 75.1 62 141.1 83 147.1 191 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 132 119.1 182 132.1 116 116.1 95.1 176 161.1 144 27 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.2 144.1 120 28.1 53 27.1 84.1 122.2 142.1 148 131 163.2 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.2 147.2 84.2 173 104 186.1 98 112 46 160.2 38.1 122.3 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 185 19.1 160.3 163.3 191.1 122.4 54 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[12]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0107363 0.3272544 -0.1109346
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.519248587 0.006705435 0.249693012
#> grade_iii, Cure model
#> 1.228471224
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 50 10.02 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 188 16.16 1 46 0 1
#> 145 10.07 1 65 1 0
#> 164 23.60 1 76 0 1
#> 91 5.33 1 61 0 1
#> 69 23.23 1 25 0 1
#> 190 20.81 1 42 1 0
#> 30 17.43 1 78 0 0
#> 139 21.49 1 63 1 0
#> 40 18.00 1 28 1 0
#> 18 15.21 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 192 16.44 1 31 1 0
#> 68 20.62 1 44 0 0
#> 26 15.77 1 49 0 1
#> 125 15.65 1 67 1 0
#> 145.1 10.07 1 65 1 0
#> 167 15.55 1 56 1 0
#> 99 21.19 1 38 0 1
#> 10 10.53 1 34 0 0
#> 37 12.52 1 57 1 0
#> 155 13.08 1 26 0 0
#> 85 16.44 1 36 0 0
#> 32 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 154 12.63 1 20 1 0
#> 81.1 14.06 1 34 0 0
#> 40.1 18.00 1 28 1 0
#> 188.1 16.16 1 46 0 1
#> 18.1 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 194 22.40 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 18.2 15.21 1 49 1 0
#> 91.1 5.33 1 61 0 1
#> 45 17.42 1 54 0 1
#> 181 16.46 1 45 0 1
#> 155.1 13.08 1 26 0 0
#> 168 23.72 1 70 0 0
#> 30.1 17.43 1 78 0 0
#> 89 11.44 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 181.1 16.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 55 19.34 1 69 0 1
#> 108 18.29 1 39 0 1
#> 36 21.19 1 48 0 1
#> 89.1 11.44 1 NA 0 0
#> 69.1 23.23 1 25 0 1
#> 149 8.37 1 33 1 0
#> 6 15.64 1 39 0 0
#> 91.2 5.33 1 61 0 1
#> 79.1 16.23 1 54 1 0
#> 190.1 20.81 1 42 1 0
#> 45.1 17.42 1 54 0 1
#> 158 20.14 1 74 1 0
#> 5 16.43 1 51 0 1
#> 171 16.57 1 41 0 1
#> 107 11.18 1 54 1 0
#> 133 14.65 1 57 0 0
#> 70 7.38 1 30 1 0
#> 93 10.33 1 52 0 1
#> 58 19.34 1 39 0 0
#> 26.1 15.77 1 49 0 1
#> 18.3 15.21 1 49 1 0
#> 36.1 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 55.1 19.34 1 69 0 1
#> 134 17.81 1 47 1 0
#> 37.1 12.52 1 57 1 0
#> 60 13.15 1 38 1 0
#> 159 10.55 1 50 0 1
#> 187.1 9.92 1 39 1 0
#> 149.1 8.37 1 33 1 0
#> 49 12.19 1 48 1 0
#> 5.1 16.43 1 51 0 1
#> 153 21.33 1 55 1 0
#> 199.1 19.81 1 NA 0 1
#> 187.2 9.92 1 39 1 0
#> 91.3 5.33 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 81.2 14.06 1 34 0 0
#> 164.1 23.60 1 76 0 1
#> 127 3.53 1 62 0 1
#> 150 20.33 1 48 0 0
#> 86 23.81 1 58 0 1
#> 129 23.41 1 53 1 0
#> 37.2 12.52 1 57 1 0
#> 111 17.45 1 47 0 1
#> 41.1 18.02 1 40 1 0
#> 129.1 23.41 1 53 1 0
#> 108.1 18.29 1 39 0 1
#> 167.1 15.55 1 56 1 0
#> 157 15.10 1 47 0 0
#> 155.2 13.08 1 26 0 0
#> 56 12.21 1 60 0 0
#> 179 18.63 1 42 0 0
#> 56.1 12.21 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 187.3 9.92 1 39 1 0
#> 16 8.71 1 71 0 1
#> 136 21.83 1 43 0 1
#> 49.1 12.19 1 48 1 0
#> 61 10.12 1 36 0 1
#> 164.2 23.60 1 76 0 1
#> 157.1 15.10 1 47 0 0
#> 133.1 14.65 1 57 0 0
#> 94 24.00 0 51 0 1
#> 196 24.00 0 19 0 0
#> 148 24.00 0 61 1 0
#> 109 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 147 24.00 0 76 1 0
#> 185 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 95 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 141 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 83 24.00 0 6 0 0
#> 152 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 156.1 24.00 0 50 1 0
#> 98.1 24.00 0 34 1 0
#> 67 24.00 0 25 0 0
#> 44 24.00 0 56 0 0
#> 148.1 24.00 0 61 1 0
#> 116 24.00 0 58 0 1
#> 165 24.00 0 47 0 0
#> 156.2 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 98.2 24.00 0 34 1 0
#> 2 24.00 0 9 0 0
#> 102 24.00 0 49 0 0
#> 121.1 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 141.1 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 174 24.00 0 49 1 0
#> 165.1 24.00 0 47 0 0
#> 182 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 98.3 24.00 0 34 1 0
#> 87 24.00 0 27 0 0
#> 156.3 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 148.2 24.00 0 61 1 0
#> 83.1 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 143 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 73.1 24.00 0 NA 0 1
#> 126 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 156.4 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 116.1 24.00 0 58 0 1
#> 178.1 24.00 0 52 1 0
#> 22 24.00 0 52 1 0
#> 2.1 24.00 0 9 0 0
#> 54.1 24.00 0 53 1 0
#> 137 24.00 0 45 1 0
#> 102.1 24.00 0 49 0 0
#> 115 24.00 0 NA 1 0
#> 1.1 24.00 0 23 1 0
#> 165.2 24.00 0 47 0 0
#> 176.1 24.00 0 43 0 1
#> 132 24.00 0 55 0 0
#> 95.1 24.00 0 68 0 1
#> 156.5 24.00 0 50 1 0
#> 119 24.00 0 17 0 0
#> 200.1 24.00 0 64 0 0
#> 74 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#> 44.1 24.00 0 56 0 0
#> 11.1 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 121.2 24.00 0 57 1 0
#> 137.1 24.00 0 45 1 0
#> 141.2 24.00 0 44 1 0
#> 82.1 24.00 0 34 0 0
#> 156.6 24.00 0 50 1 0
#> 64.1 24.00 0 43 0 0
#> 137.2 24.00 0 45 1 0
#> 161.1 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.519 NA NA NA
#> 2 age, Cure model 0.00671 NA NA NA
#> 3 grade_ii, Cure model 0.250 NA NA NA
#> 4 grade_iii, Cure model 1.23 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0107 NA NA NA
#> 2 grade_ii, Survival model 0.327 NA NA NA
#> 3 grade_iii, Survival model -0.111 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.519249 0.006705 0.249693 1.228471
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 248.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.519248587 0.006705435 0.249693012 1.228471224
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0107363 0.3272544 -0.1109346
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8232176098 0.3328810464 0.3534720640 0.7830791088 0.0040726447
#> [6] 0.9306086848 0.0187524737 0.0751682610 0.2273041924 0.0411020924
#> [11] 0.1850601686 0.4411193714 0.5325788323 0.2928777929 0.0873595209
#> [16] 0.3746224201 0.3963509090 0.7830791088 0.4186909119 0.0519471875
#> [21] 0.7434648553 0.6296671643 0.5807363804 0.2928777929 0.0689283346
#> [26] 0.1074091117 0.6172703918 0.5325788323 0.1850601686 0.3534720640
#> [31] 0.4411193714 0.8097344985 0.0265641281 0.4411193714 0.9306086848
#> [36] 0.2452095437 0.2733988828 0.5807363804 0.0021941241 0.2273041924
#> [41] 0.0311038105 0.2733988828 0.0002036727 0.1144827585 0.1522144905
#> [46] 0.0519471875 0.0187524737 0.8897994651 0.4074685276 0.9306086848
#> [51] 0.3328810464 0.0751682610 0.2452095437 0.1005500707 0.3125706858
#> [56] 0.2637919939 0.7175141773 0.5088587992 0.9169383670 0.7565653652
#> [61] 0.1144827585 0.3746224201 0.4411193714 0.0519471875 0.1685590347
#> [66] 0.1144827585 0.2015226747 0.6296671643 0.5684857349 0.7304345689
#> [71] 0.8232176098 0.8897994651 0.6920076243 0.3125706858 0.0464511231
#> [76] 0.8232176098 0.9306086848 0.1441759671 0.5325788323 0.0040726447
#> [81] 0.9857944094 0.0938614462 0.0009162512 0.0118715147 0.6296671643
#> [86] 0.2185666014 0.1685590347 0.0118715147 0.1522144905 0.4186909119
#> [91] 0.4856343897 0.5807363804 0.6666613403 0.1363112677 0.6666613403
#> [96] 0.2099866938 0.8232176098 0.8761361758 0.0359512534 0.6920076243
#> [101] 0.7697774975 0.0040726447 0.4856343897 0.5088587992 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 187 79 188 145 164 91 69 190 30 139 40 18 81
#> 9.92 16.23 16.16 10.07 23.60 5.33 23.23 20.81 17.43 21.49 18.00 15.21 14.06
#> 192 68 26 125 145.1 167 99 10 37 155 85 32 105
#> 16.44 20.62 15.77 15.65 10.07 15.55 21.19 10.53 12.52 13.08 16.44 20.90 19.75
#> 154 81.1 40.1 188.1 18.1 101 194 18.2 91.1 45 181 155.1 168
#> 12.63 14.06 18.00 16.16 15.21 9.97 22.40 15.21 5.33 17.42 16.46 13.08 23.72
#> 30.1 66 181.1 24 55 108 36 69.1 149 6 91.2 79.1 190.1
#> 17.43 22.13 16.46 23.89 19.34 18.29 21.19 23.23 8.37 15.64 5.33 16.23 20.81
#> 45.1 158 5 171 107 133 70 93 58 26.1 18.3 36.1 41
#> 17.42 20.14 16.43 16.57 11.18 14.65 7.38 10.33 19.34 15.77 15.21 21.19 18.02
#> 55.1 134 37.1 60 159 187.1 149.1 49 5.1 153 187.2 91.3 88
#> 19.34 17.81 12.52 13.15 10.55 9.92 8.37 12.19 16.43 21.33 9.92 5.33 18.37
#> 81.2 164.1 127 150 86 129 37.2 111 41.1 129.1 108.1 167.1 157
#> 14.06 23.60 3.53 20.33 23.81 23.41 12.52 17.45 18.02 23.41 18.29 15.55 15.10
#> 155.2 56 179 56.1 184 187.3 16 136 49.1 61 164.2 157.1 133.1
#> 13.08 12.21 18.63 12.21 17.77 9.92 8.71 21.83 12.19 10.12 23.60 15.10 14.65
#> 94 196 148 109 20 147 185 98 95 178 121 176 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 46 83 152 156 82 156.1 98.1 67 44 148.1 116 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 17 161 98.2 2 102 121.1 65 104 141.1 200 174 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 1 98.3 87 156.3 35 148.2 83.1 33 103 143 54 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 143.1 156.4 11 116.1 178.1 22 2.1 54.1 137 102.1 1.1 165.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 132 95.1 156.5 119 200.1 74 119.1 44.1 11.1 146 121.2 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 82.1 156.6 64.1 137.2 161.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[13]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00611739 -0.09163203 0.26613394
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.83710370 0.01586879 0.14720833
#> grade_iii, Cure model
#> 0.77962766
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 111 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 153 21.33 1 55 1 0
#> 190 20.81 1 42 1 0
#> 43 12.10 1 61 0 1
#> 77 7.27 1 67 0 1
#> 45 17.42 1 54 0 1
#> 170 19.54 1 43 0 1
#> 63 22.77 1 31 1 0
#> 10 10.53 1 34 0 0
#> 197 21.60 1 69 1 0
#> 93 10.33 1 52 0 1
#> 133 14.65 1 57 0 0
#> 195 11.76 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 133.1 14.65 1 57 0 0
#> 105 19.75 1 60 0 0
#> 124 9.73 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 158.1 20.14 1 74 1 0
#> 150 20.33 1 48 0 0
#> 93.1 10.33 1 52 0 1
#> 106 16.67 1 49 1 0
#> 51 18.23 1 83 0 1
#> 125 15.65 1 67 1 0
#> 15 22.68 1 48 0 0
#> 32 20.90 1 37 1 0
#> 110 17.56 1 65 0 1
#> 23 16.92 1 61 0 0
#> 6 15.64 1 39 0 0
#> 175 21.91 1 43 0 0
#> 32.1 20.90 1 37 1 0
#> 190.1 20.81 1 42 1 0
#> 157 15.10 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 194 22.40 1 38 0 1
#> 169 22.41 1 46 0 0
#> 113 22.86 1 34 0 0
#> 81 14.06 1 34 0 0
#> 86 23.81 1 58 0 1
#> 158.2 20.14 1 74 1 0
#> 91 5.33 1 61 0 1
#> 170.1 19.54 1 43 0 1
#> 129 23.41 1 53 1 0
#> 153.1 21.33 1 55 1 0
#> 125.1 15.65 1 67 1 0
#> 145 10.07 1 65 1 0
#> 30.1 17.43 1 78 0 0
#> 169.1 22.41 1 46 0 0
#> 159 10.55 1 50 0 1
#> 97 19.14 1 65 0 1
#> 106.1 16.67 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 100 16.07 1 60 0 0
#> 59.1 10.16 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 18 15.21 1 49 1 0
#> 153.2 21.33 1 55 1 0
#> 66 22.13 1 53 0 0
#> 100.1 16.07 1 60 0 0
#> 177 12.53 1 75 0 0
#> 133.2 14.65 1 57 0 0
#> 170.2 19.54 1 43 0 1
#> 6.1 15.64 1 39 0 0
#> 158.3 20.14 1 74 1 0
#> 60 13.15 1 38 1 0
#> 157.1 15.10 1 47 0 0
#> 36 21.19 1 48 0 1
#> 81.1 14.06 1 34 0 0
#> 91.1 5.33 1 61 0 1
#> 23.1 16.92 1 61 0 0
#> 164 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 107 11.18 1 54 1 0
#> 177.1 12.53 1 75 0 0
#> 50 10.02 1 NA 1 0
#> 155.1 13.08 1 26 0 0
#> 127 3.53 1 62 0 1
#> 100.2 16.07 1 60 0 0
#> 140 12.68 1 59 1 0
#> 93.2 10.33 1 52 0 1
#> 85 16.44 1 36 0 0
#> 61 10.12 1 36 0 1
#> 81.2 14.06 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 78 23.88 1 43 0 0
#> 197.1 21.60 1 69 1 0
#> 16 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 85.1 16.44 1 36 0 0
#> 63.1 22.77 1 31 1 0
#> 129.1 23.41 1 53 1 0
#> 25 6.32 1 34 1 0
#> 66.1 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 169.2 22.41 1 46 0 0
#> 81.3 14.06 1 34 0 0
#> 93.3 10.33 1 52 0 1
#> 13 14.34 1 54 0 1
#> 29 15.45 1 68 1 0
#> 139 21.49 1 63 1 0
#> 63.2 22.77 1 31 1 0
#> 93.4 10.33 1 52 0 1
#> 195.1 11.76 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 78.1 23.88 1 43 0 0
#> 187 9.92 1 39 1 0
#> 61.1 10.12 1 36 0 1
#> 198 24.00 0 66 0 1
#> 146 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 64.1 24.00 0 43 0 0
#> 62 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 193 24.00 0 45 0 1
#> 46 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 46.1 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 182 24.00 0 35 0 0
#> 135.1 24.00 0 58 1 0
#> 2 24.00 0 9 0 0
#> 200 24.00 0 64 0 0
#> 156 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 141 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 33 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 102 24.00 0 49 0 0
#> 83 24.00 0 6 0 0
#> 21 24.00 0 47 0 0
#> 137.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 67 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 147 24.00 0 76 1 0
#> 198.1 24.00 0 66 0 1
#> 126 24.00 0 48 0 0
#> 17.1 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 102.1 24.00 0 49 0 0
#> 73 24.00 0 NA 0 1
#> 163 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 115.1 24.00 0 NA 1 0
#> 62.1 24.00 0 71 0 0
#> 200.1 24.00 0 64 0 0
#> 182.1 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 121.1 24.00 0 57 1 0
#> 160 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 137.2 24.00 0 45 1 0
#> 31.1 24.00 0 36 0 1
#> 48.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 82.1 24.00 0 34 0 0
#> 20 24.00 0 46 1 0
#> 198.2 24.00 0 66 0 1
#> 160.1 24.00 0 31 1 0
#> 31.2 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 198.3 24.00 0 66 0 1
#> 38 24.00 0 31 1 0
#> 121.2 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 102.2 24.00 0 49 0 0
#> 87.1 24.00 0 27 0 0
#> 131.1 24.00 0 66 0 0
#> 126.1 24.00 0 48 0 0
#> 146.1 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 196 24.00 0 19 0 0
#> 54 24.00 0 53 1 0
#> 151 24.00 0 42 0 0
#> 102.3 24.00 0 49 0 0
#> 9 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 67.1 24.00 0 25 0 0
#> 84 24.00 0 39 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.837 NA NA NA
#> 2 age, Cure model 0.0159 NA NA NA
#> 3 grade_ii, Cure model 0.147 NA NA NA
#> 4 grade_iii, Cure model 0.780 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00612 NA NA NA
#> 2 grade_ii, Survival model -0.0916 NA NA NA
#> 3 grade_iii, Survival model 0.266 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83710 0.01587 0.14721 0.77963
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 250.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83710370 0.01586879 0.14720833 0.77962766
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00611739 -0.09163203 0.26613394
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.57208874 0.55439572 0.34738452 0.42112903 0.86850839 0.96636484
#> [7] 0.59769935 0.50911326 0.17740633 0.89029908 0.31365359 0.89751304
#> [13] 0.75711301 0.58077126 0.75711301 0.49949331 0.46179835 0.46179835
#> [19] 0.45170220 0.89751304 0.62265620 0.54547189 0.69507097 0.21632922
#> [25] 0.40055067 0.56330767 0.60612616 0.71070171 0.30188721 0.40055067
#> [31] 0.42112903 0.74177996 0.14831284 0.26621473 0.22987480 0.16300910
#> [37] 0.78725740 0.08158572 0.46179835 0.97995718 0.50911326 0.11894456
#> [43] 0.34738452 0.69507097 0.94572021 0.58077126 0.22987480 0.88307159
#> [49] 0.53637419 0.62265620 0.39004711 0.66343057 0.82422067 0.73401969
#> [55] 0.34738452 0.27854489 0.66343057 0.85388062 0.75711301 0.50911326
#> [61] 0.71070171 0.46179835 0.81675466 0.74177996 0.37932064 0.78725740
#> [67] 0.97995718 0.60612616 0.10207890 0.44152845 0.87579815 0.85388062
#> [73] 0.82422067 0.99333118 0.66343057 0.83903900 0.89751304 0.64726826
#> [79] 0.93192778 0.78725740 0.63908537 0.03782420 0.31365359 0.95951921
#> [85] 0.84646082 0.64726826 0.17740633 0.11894456 0.97316394 0.27854489
#> [91] 0.22987480 0.78725740 0.89751304 0.77971087 0.72624040 0.33609885
#> [97] 0.17740633 0.89751304 0.68714399 0.03782420 0.95262366 0.93192778
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 111 40 153 190 43 77 45 170 63 10 197 93 133
#> 17.45 18.00 21.33 20.81 12.10 7.27 17.42 19.54 22.77 10.53 21.60 10.33 14.65
#> 30 133.1 105 158 158.1 150 93.1 106 51 125 15 32 110
#> 17.43 14.65 19.75 20.14 20.14 20.33 10.33 16.67 18.23 15.65 22.68 20.90 17.56
#> 23 6 175 32.1 190.1 157 69 194 169 113 81 86 158.2
#> 16.92 15.64 21.91 20.90 20.81 15.10 23.23 22.40 22.41 22.86 14.06 23.81 20.14
#> 91 170.1 129 153.1 125.1 145 30.1 169.1 159 97 106.1 90 100
#> 5.33 19.54 23.41 21.33 15.65 10.07 17.43 22.41 10.55 19.14 16.67 20.94 16.07
#> 155 18 153.2 66 100.1 177 133.2 170.2 6.1 158.3 60 157.1 36
#> 13.08 15.21 21.33 22.13 16.07 12.53 14.65 19.54 15.64 20.14 13.15 15.10 21.19
#> 81.1 91.1 23.1 164 128 107 177.1 155.1 127 100.2 140 93.2 85
#> 14.06 5.33 16.92 23.60 20.35 11.18 12.53 13.08 3.53 16.07 12.68 10.33 16.44
#> 61 81.2 130 78 197.1 16 154 85.1 63.1 129.1 25 66.1 169.2
#> 10.12 14.06 16.47 23.88 21.60 8.71 12.63 16.44 22.77 23.41 6.32 22.13 22.41
#> 81.3 93.3 13 29 139 63.2 93.4 26 78.1 187 61.1 198 146
#> 14.06 10.33 14.34 15.45 21.49 22.77 10.33 15.77 23.88 9.92 10.12 24.00 24.00
#> 64 121 64.1 62 137 109 193 46 122 74 17 112 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 87 182 135.1 2 200 156 7 141 161 33 31 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 21 137.1 48 80 22 142 103 82 67 138 103.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 126 17.1 131 102.1 163 19 62.1 200.1 182.1 132 121.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 137.2 31.1 48.1 104 82.1 20 198.2 160.1 31.2 165 198.3 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.2 178 141.1 102.2 87.1 131.1 126.1 146.1 1 196 54 151 102.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 165.1 95 67.1 84
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[14]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0005189823 0.1953977647 0.3916804911
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.90773959 0.02139442 -0.07751832
#> grade_iii, Cure model
#> 0.39039195
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 88 18.37 1 47 0 0
#> 97 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 55 19.34 1 69 0 1
#> 179 18.63 1 42 0 0
#> 52 10.42 1 52 0 1
#> 18 15.21 1 49 1 0
#> 133 14.65 1 57 0 0
#> 177 12.53 1 75 0 0
#> 107 11.18 1 54 1 0
#> 70 7.38 1 30 1 0
#> 107.1 11.18 1 54 1 0
#> 40 18.00 1 28 1 0
#> 101 9.97 1 10 0 1
#> 90 20.94 1 50 0 1
#> 154 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 70.1 7.38 1 30 1 0
#> 167 15.55 1 56 1 0
#> 50 10.02 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 66 22.13 1 53 0 0
#> 175 21.91 1 43 0 0
#> 90.1 20.94 1 50 0 1
#> 30 17.43 1 78 0 0
#> 124.1 9.73 1 NA 1 0
#> 97.1 19.14 1 65 0 1
#> 10 10.53 1 34 0 0
#> 177.1 12.53 1 75 0 0
#> 63 22.77 1 31 1 0
#> 23 16.92 1 61 0 0
#> 158 20.14 1 74 1 0
#> 61 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 108 18.29 1 39 0 1
#> 190 20.81 1 42 1 0
#> 150 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 40.1 18.00 1 28 1 0
#> 93 10.33 1 52 0 1
#> 29 15.45 1 68 1 0
#> 169 22.41 1 46 0 0
#> 194 22.40 1 38 0 1
#> 88.1 18.37 1 47 0 0
#> 50.1 10.02 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 92.1 22.92 1 47 0 1
#> 101.2 9.97 1 10 0 1
#> 52.1 10.42 1 52 0 1
#> 24 23.89 1 38 0 0
#> 37 12.52 1 57 1 0
#> 101.3 9.97 1 10 0 1
#> 189 10.51 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 81 14.06 1 34 0 0
#> 123 13.00 1 44 1 0
#> 92.2 22.92 1 47 0 1
#> 91 5.33 1 61 0 1
#> 157 15.10 1 47 0 0
#> 39 15.59 1 37 0 1
#> 49 12.19 1 48 1 0
#> 43 12.10 1 61 0 1
#> 192.1 16.44 1 31 1 0
#> 49.1 12.19 1 48 1 0
#> 51 18.23 1 83 0 1
#> 117 17.46 1 26 0 1
#> 136 21.83 1 43 0 1
#> 97.2 19.14 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 177.2 12.53 1 75 0 0
#> 169.1 22.41 1 46 0 0
#> 39.1 15.59 1 37 0 1
#> 39.2 15.59 1 37 0 1
#> 88.2 18.37 1 47 0 0
#> 189.2 10.51 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 77 7.27 1 67 0 1
#> 153.1 21.33 1 55 1 0
#> 26 15.77 1 49 0 1
#> 78 23.88 1 43 0 0
#> 52.2 10.42 1 52 0 1
#> 36 21.19 1 48 0 1
#> 125 15.65 1 67 1 0
#> 88.3 18.37 1 47 0 0
#> 57 14.46 1 45 0 1
#> 63.1 22.77 1 31 1 0
#> 10.1 10.53 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 91.1 5.33 1 61 0 1
#> 101.4 9.97 1 10 0 1
#> 170 19.54 1 43 0 1
#> 184 17.77 1 38 0 0
#> 93.1 10.33 1 52 0 1
#> 15 22.68 1 48 0 0
#> 91.2 5.33 1 61 0 1
#> 129 23.41 1 53 1 0
#> 183 9.24 1 67 1 0
#> 30.1 17.43 1 78 0 0
#> 97.3 19.14 1 65 0 1
#> 129.1 23.41 1 53 1 0
#> 187 9.92 1 39 1 0
#> 100.1 16.07 1 60 0 0
#> 77.1 7.27 1 67 0 1
#> 106 16.67 1 49 1 0
#> 184.1 17.77 1 38 0 0
#> 52.3 10.42 1 52 0 1
#> 139 21.49 1 63 1 0
#> 37.1 12.52 1 57 1 0
#> 63.2 22.77 1 31 1 0
#> 160 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 151 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 72 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 151.1 24.00 0 42 0 0
#> 121 24.00 0 57 1 0
#> 27.1 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 47 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 148 24.00 0 61 1 0
#> 80 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 161.1 24.00 0 45 0 0
#> 67 24.00 0 25 0 0
#> 7 24.00 0 37 1 0
#> 94 24.00 0 51 0 1
#> 31 24.00 0 36 0 1
#> 73 24.00 0 NA 0 1
#> 87 24.00 0 27 0 0
#> 80.2 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 173.1 24.00 0 19 0 1
#> 47.1 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 95 24.00 0 68 0 1
#> 151.2 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 148.1 24.00 0 61 1 0
#> 176.1 24.00 0 43 0 1
#> 185.1 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 122 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 11.1 24.00 0 42 0 1
#> 193.1 24.00 0 45 0 1
#> 121.1 24.00 0 57 1 0
#> 95.1 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 31.1 24.00 0 36 0 1
#> 98.1 24.00 0 34 1 0
#> 137 24.00 0 45 1 0
#> 121.2 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 104.1 24.00 0 50 1 0
#> 1.1 24.00 0 23 1 0
#> 142.1 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 19.1 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 104.2 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 7.1 24.00 0 37 1 0
#> 19.2 24.00 0 57 0 1
#> 3.1 24.00 0 31 1 0
#> 98.2 24.00 0 34 1 0
#> 173.2 24.00 0 19 0 1
#> 3.2 24.00 0 31 1 0
#> 121.3 24.00 0 57 1 0
#> 173.3 24.00 0 19 0 1
#> 27.2 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 191 24.00 0 60 0 1
#> 75 24.00 0 21 1 0
#> 172 24.00 0 41 0 0
#> 80.3 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 118 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 160.1 24.00 0 31 1 0
#> 47.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.908 NA NA NA
#> 2 age, Cure model 0.0214 NA NA NA
#> 3 grade_ii, Cure model -0.0775 NA NA NA
#> 4 grade_iii, Cure model 0.390 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000519 NA NA NA
#> 2 grade_ii, Survival model 0.195 NA NA NA
#> 3 grade_iii, Survival model 0.392 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.90774 0.02139 -0.07752 0.39039
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 256.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.90773959 0.02139442 -0.07751832 0.39039195
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0005189823 0.1953977647 0.3916804911
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.26011757 0.42075192 0.36529136 0.41129532 0.35523756 0.40183508
#> [7] 0.84051685 0.66844964 0.68523124 0.73502992 0.80838571 0.94787215
#> [13] 0.80838571 0.47577031 0.89511817 0.29302180 0.71859418 0.58300483
#> [19] 0.94787215 0.65158529 0.89511817 0.21326565 0.22517242 0.29302180
#> [25] 0.52991069 0.36529136 0.82445406 0.73502992 0.13060561 0.54764264
#> [31] 0.33466460 0.88731951 0.09389194 0.45724580 0.31375549 0.32421428
#> [37] 0.56547583 0.47577031 0.87172148 0.66003144 0.17750046 0.20134050
#> [43] 0.42075192 0.59176783 0.09389194 0.89511817 0.84051685 0.01389775
#> [49] 0.75951285 0.89511817 0.51192542 0.70195228 0.71028511 0.09389194
#> [55] 0.97791407 0.67684172 0.62649309 0.78403644 0.80027063 0.56547583
#> [61] 0.78403644 0.46655812 0.52095682 0.23706514 0.36529136 0.73502992
#> [67] 0.17750046 0.62649309 0.62649309 0.42075192 0.77583482 0.96295541
#> [73] 0.26011757 0.60914794 0.03704743 0.84051685 0.28205557 0.61783627
#> [79] 0.42075192 0.69361768 0.13060561 0.82445406 0.71859418 0.97791407
#> [85] 0.89511817 0.34502970 0.49385441 0.87172148 0.16511181 0.97791407
#> [91] 0.06044892 0.94027176 0.52991069 0.36529136 0.06044892 0.93265544
#> [97] 0.59176783 0.96295541 0.55657689 0.49385441 0.84051685 0.24865973
#> [103] 0.75951285 0.13060561 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 153 88 97 8 55 179 52 18 133 177 107 70 107.1
#> 21.33 18.37 19.14 18.43 19.34 18.63 10.42 15.21 14.65 12.53 11.18 7.38 11.18
#> 40 101 90 154 188 70.1 167 101.1 66 175 90.1 30 97.1
#> 18.00 9.97 20.94 12.63 16.16 7.38 15.55 9.97 22.13 21.91 20.94 17.43 19.14
#> 10 177.1 63 23 158 61 92 108 190 150 192 40.1 93
#> 10.53 12.53 22.77 16.92 20.14 10.12 22.92 18.29 20.81 20.33 16.44 18.00 10.33
#> 29 169 194 88.1 100 92.1 101.2 52.1 24 37 101.3 110 81
#> 15.45 22.41 22.40 18.37 16.07 22.92 9.97 10.42 23.89 12.52 9.97 17.56 14.06
#> 123 92.2 91 157 39 49 43 192.1 49.1 51 117 136 97.2
#> 13.00 22.92 5.33 15.10 15.59 12.19 12.10 16.44 12.19 18.23 17.46 21.83 19.14
#> 177.2 169.1 39.1 39.2 88.2 56 77 153.1 26 78 52.2 36 125
#> 12.53 22.41 15.59 15.59 18.37 12.21 7.27 21.33 15.77 23.88 10.42 21.19 15.65
#> 88.3 57 63.1 10.1 154.1 91.1 101.4 170 184 93.1 15 91.2 129
#> 18.37 14.46 22.77 10.53 12.63 5.33 9.97 19.54 17.77 10.33 22.68 5.33 23.41
#> 183 30.1 97.3 129.1 187 100.1 77.1 106 184.1 52.3 139 37.1 63.2
#> 9.24 17.43 19.14 23.41 9.92 16.07 7.27 16.67 17.77 10.42 21.49 12.52 22.77
#> 160 193 151 11 72 27 33 178 151.1 121 27.1 116 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 53 161 185 173 148 80 141 80.1 176 161.1 67 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 31 87 80.2 152 1 173.1 47.1 98 95 151.2 104 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 176.1 185.1 200 122 19 11.1 193.1 121.1 95.1 9 31.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 121.2 142 104.1 1.1 142.1 35 35.1 162 19.1 196 62 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 74 7.1 19.2 3.1 98.2 173.2 3.2 121.3 173.3 27.2 102 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 172 80.3 119 118 118.1 109 160.1 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[15]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0173782 0.7353625 0.4458821
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.598406348 0.008776202 0.224268444
#> grade_iii, Cure model
#> 0.697393616
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 125 15.65 1 67 1 0
#> 164 23.60 1 76 0 1
#> 183 9.24 1 67 1 0
#> 13 14.34 1 54 0 1
#> 192 16.44 1 31 1 0
#> 170 19.54 1 43 0 1
#> 29 15.45 1 68 1 0
#> 101 9.97 1 10 0 1
#> 177 12.53 1 75 0 0
#> 171 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 42 12.43 1 49 0 1
#> 8 18.43 1 32 0 0
#> 93 10.33 1 52 0 1
#> 93.1 10.33 1 52 0 1
#> 164.1 23.60 1 76 0 1
#> 164.2 23.60 1 76 0 1
#> 101.1 9.97 1 10 0 1
#> 81 14.06 1 34 0 0
#> 13.1 14.34 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 41 18.02 1 40 1 0
#> 50 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 4 17.64 1 NA 0 1
#> 70 7.38 1 30 1 0
#> 100 16.07 1 60 0 0
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 183.1 9.24 1 67 1 0
#> 96 14.54 1 33 0 1
#> 127 3.53 1 62 0 1
#> 8.1 18.43 1 32 0 0
#> 145 10.07 1 65 1 0
#> 125.1 15.65 1 67 1 0
#> 50.1 10.02 1 NA 1 0
#> 108.1 18.29 1 39 0 1
#> 110 17.56 1 65 0 1
#> 68 20.62 1 44 0 0
#> 158 20.14 1 74 1 0
#> 99 21.19 1 38 0 1
#> 91 5.33 1 61 0 1
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 145.1 10.07 1 65 1 0
#> 154 12.63 1 20 1 0
#> 149 8.37 1 33 1 0
#> 125.2 15.65 1 67 1 0
#> 167 15.55 1 56 1 0
#> 189.1 10.51 1 NA 1 0
#> 68.1 20.62 1 44 0 0
#> 89 11.44 1 NA 0 0
#> 130.1 16.47 1 53 0 1
#> 10 10.53 1 34 0 0
#> 93.2 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 154.1 12.63 1 20 1 0
#> 76 19.22 1 54 0 1
#> 40 18.00 1 28 1 0
#> 81.1 14.06 1 34 0 0
#> 157 15.10 1 47 0 0
#> 107 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 189.2 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 14 12.89 1 21 0 0
#> 77 7.27 1 67 0 1
#> 30 17.43 1 78 0 0
#> 40.1 18.00 1 28 1 0
#> 133 14.65 1 57 0 0
#> 167.1 15.55 1 56 1 0
#> 6 15.64 1 39 0 0
#> 159 10.55 1 50 0 1
#> 136 21.83 1 43 0 1
#> 124 9.73 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 108.2 18.29 1 39 0 1
#> 149.1 8.37 1 33 1 0
#> 157.1 15.10 1 47 0 0
#> 158.1 20.14 1 74 1 0
#> 49 12.19 1 48 1 0
#> 171.1 16.57 1 41 0 1
#> 60.1 13.15 1 38 1 0
#> 199 19.81 1 NA 0 1
#> 61 10.12 1 36 0 1
#> 79 16.23 1 54 1 0
#> 167.2 15.55 1 56 1 0
#> 60.2 13.15 1 38 1 0
#> 199.1 19.81 1 NA 0 1
#> 113.1 22.86 1 34 0 0
#> 189.3 10.51 1 NA 1 0
#> 93.3 10.33 1 52 0 1
#> 113.2 22.86 1 34 0 0
#> 139 21.49 1 63 1 0
#> 153 21.33 1 55 1 0
#> 107.1 11.18 1 54 1 0
#> 29.1 15.45 1 68 1 0
#> 41.1 18.02 1 40 1 0
#> 81.2 14.06 1 34 0 0
#> 52 10.42 1 52 0 1
#> 168 23.72 1 70 0 0
#> 76.1 19.22 1 54 0 1
#> 18.1 15.21 1 49 1 0
#> 4.1 17.64 1 NA 0 1
#> 91.1 5.33 1 61 0 1
#> 117 17.46 1 26 0 1
#> 127.1 3.53 1 62 0 1
#> 160 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 19 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 186 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 112 24.00 0 61 0 0
#> 148 24.00 0 61 1 0
#> 35 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 72 24.00 0 40 0 1
#> 172 24.00 0 41 0 0
#> 28.1 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 161 24.00 0 45 0 0
#> 11 24.00 0 42 0 1
#> 71 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 174 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 182 24.00 0 35 0 0
#> 103 24.00 0 56 1 0
#> 27 24.00 0 63 1 0
#> 182.1 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 116 24.00 0 58 0 1
#> 185 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 72.1 24.00 0 40 0 1
#> 126.1 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 160.1 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 19.1 24.00 0 57 0 1
#> 9.1 24.00 0 31 1 0
#> 196.2 24.00 0 19 0 0
#> 116.1 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 102 24.00 0 49 0 0
#> 75 24.00 0 21 1 0
#> 182.2 24.00 0 35 0 0
#> 35.1 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 27.1 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 98 24.00 0 34 1 0
#> 132 24.00 0 55 0 0
#> 34.1 24.00 0 36 0 0
#> 83 24.00 0 6 0 0
#> 174.1 24.00 0 49 1 0
#> 144 24.00 0 28 0 1
#> 193.1 24.00 0 45 0 1
#> 151 24.00 0 42 0 0
#> 95 24.00 0 68 0 1
#> 27.2 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 141 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 182.3 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 17 24.00 0 38 0 1
#> 38.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 75.1 24.00 0 21 1 0
#> 95.1 24.00 0 68 0 1
#> 65.1 24.00 0 57 1 0
#> 142.1 24.00 0 53 0 0
#> 132.1 24.00 0 55 0 0
#> 144.1 24.00 0 28 0 1
#> 135.1 24.00 0 58 1 0
#> 135.2 24.00 0 58 1 0
#> 31 24.00 0 36 0 1
#> 193.2 24.00 0 45 0 1
#> 122 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.598 NA NA NA
#> 2 age, Cure model 0.00878 NA NA NA
#> 3 grade_ii, Cure model 0.224 NA NA NA
#> 4 grade_iii, Cure model 0.697 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0174 NA NA NA
#> 2 grade_ii, Survival model 0.735 NA NA NA
#> 3 grade_iii, Survival model 0.446 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.598406 0.008776 0.224268 0.697394
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.6
#> Residual Deviance: 253.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.598406348 0.008776202 0.224268444 0.697393616
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0173782 0.7353625 0.4458821
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 3.090606e-01 9.474462e-04 8.515630e-01 4.849049e-01 2.788145e-01
#> [6] 7.627739e-02 3.824733e-01 8.250216e-01 6.189260e-01 2.303182e-01
#> [11] 2.022430e-01 1.161587e-01 6.313731e-01 9.946219e-02 7.328420e-01
#> [16] 7.328420e-01 9.474462e-04 9.474462e-04 8.250216e-01 5.088969e-01
#> [21] 4.849049e-01 3.779139e-02 1.413804e-01 2.208291e-01 9.050863e-01
#> [26] 2.988088e-01 5.536468e-02 4.494185e-01 8.515630e-01 4.729891e-01
#> [31] 9.725459e-01 9.946219e-02 7.982105e-01 3.090606e-01 1.161587e-01
#> [36] 1.842153e-01 4.337150e-02 6.216962e-02 3.220827e-02 9.454500e-01
#> [41] 2.492641e-01 4.044800e-01 7.982105e-01 5.946343e-01 8.783963e-01
#> [46] 3.090606e-01 3.505937e-01 4.337150e-02 2.492641e-01 6.942126e-01
#> [51] 7.328420e-01 9.319820e-01 5.946343e-01 8.388445e-02 1.586548e-01
#> [56] 5.088969e-01 4.266190e-01 6.564551e-01 1.754160e-01 5.456021e-01
#> [61] 2.687712e-01 6.587749e-03 5.821171e-01 9.184837e-01 2.113844e-01
#> [66] 1.586548e-01 4.611091e-01 3.505937e-01 3.398420e-01 6.814944e-01
#> [71] 1.678025e-02 6.942126e-01 1.161587e-01 8.783963e-01 4.266190e-01
#> [76] 6.216962e-02 6.439026e-01 2.303182e-01 5.456021e-01 7.848380e-01
#> [81] 2.887799e-01 3.505937e-01 5.456021e-01 6.587749e-03 7.328420e-01
#> [86] 6.587749e-03 2.161681e-02 2.680772e-02 6.564551e-01 3.824733e-01
#> [91] 1.413804e-01 5.088969e-01 7.198309e-01 3.241118e-05 8.388445e-02
#> [96] 4.044800e-01 9.454500e-01 1.932279e-01 9.725459e-01 0.000000e+00
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 125 164 183 13 192 170 29 101 177 171 111 108 42
#> 15.65 23.60 9.24 14.34 16.44 19.54 15.45 9.97 12.53 16.57 17.45 18.29 12.43
#> 8 93 93.1 164.1 164.2 101.1 81 13.1 190 41 106 70 100
#> 18.43 10.33 10.33 23.60 23.60 9.97 14.06 14.34 20.81 18.02 16.67 7.38 16.07
#> 150 180 183.1 96 127 8.1 145 125.1 108.1 110 68 158 99
#> 20.33 14.82 9.24 14.54 3.53 18.43 10.07 15.65 18.29 17.56 20.62 20.14 21.19
#> 91 130 18 145.1 154 149 125.2 167 68.1 130.1 10 93.2 25
#> 5.33 16.47 15.21 10.07 12.63 8.37 15.65 15.55 20.62 16.47 10.53 10.33 6.32
#> 154.1 76 40 81.1 157 107 184 60 181 113 14 77 30
#> 12.63 19.22 18.00 14.06 15.10 11.18 17.77 13.15 16.46 22.86 12.89 7.27 17.43
#> 40.1 133 167.1 6 159 136 10.1 108.2 149.1 157.1 158.1 49 171.1
#> 18.00 14.65 15.55 15.64 10.55 21.83 10.53 18.29 8.37 15.10 20.14 12.19 16.57
#> 60.1 61 79 167.2 60.2 113.1 93.3 113.2 139 153 107.1 29.1 41.1
#> 13.15 10.12 16.23 15.55 13.15 22.86 10.33 22.86 21.49 21.33 11.18 15.45 18.02
#> 81.2 52 168 76.1 18.1 91.1 117 127.1 160 176 193 19 28
#> 14.06 10.42 23.72 19.22 15.21 5.33 17.46 3.53 24.00 24.00 24.00 24.00 24.00
#> 186 156 67 112 148 35 198 72 172 28.1 135 161 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 148.1 174 34 182 103 27 182.1 47 196 116 185 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 138 126 72.1 126.1 120 9 196.1 160.1 38 137.1 33 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 196.2 116.1 21 118 103.1 102 75 182.2 35.1 22 121 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 178 98 132 34.1 83 174.1 144 193.1 151 95 27.2 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 142 182.3 173 17 38.1 162 75.1 95.1 65.1 142.1 132.1 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 135.2 31 193.2 122
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[16]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004144199 0.837147326 0.690855349
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.84077007 0.01560229 0.48387407
#> grade_iii, Cure model
#> 0.34823218
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 111 17.45 1 47 0 1
#> 92 22.92 1 47 0 1
#> 107 11.18 1 54 1 0
#> 60 13.15 1 38 1 0
#> 51 18.23 1 83 0 1
#> 158 20.14 1 74 1 0
#> 42 12.43 1 49 0 1
#> 145 10.07 1 65 1 0
#> 106 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 77 7.27 1 67 0 1
#> 113 22.86 1 34 0 0
#> 171 16.57 1 41 0 1
#> 97 19.14 1 65 0 1
#> 24 23.89 1 38 0 0
#> 36 21.19 1 48 0 1
#> 149 8.37 1 33 1 0
#> 77.1 7.27 1 67 0 1
#> 149.1 8.37 1 33 1 0
#> 39 15.59 1 37 0 1
#> 175 21.91 1 43 0 0
#> 66 22.13 1 53 0 0
#> 167 15.55 1 56 1 0
#> 14 12.89 1 21 0 0
#> 180 14.82 1 37 0 0
#> 149.2 8.37 1 33 1 0
#> 18 15.21 1 49 1 0
#> 52 10.42 1 52 0 1
#> 128 20.35 1 35 0 1
#> 166 19.98 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 108 18.29 1 39 0 1
#> 179 18.63 1 42 0 0
#> 167.1 15.55 1 56 1 0
#> 187 9.92 1 39 1 0
#> 153 21.33 1 55 1 0
#> 113.1 22.86 1 34 0 0
#> 70 7.38 1 30 1 0
#> 117 17.46 1 26 0 1
#> 93 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 79 16.23 1 54 1 0
#> 15 22.68 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 15.1 22.68 1 48 0 0
#> 128.1 20.35 1 35 0 1
#> 14.1 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 16 8.71 1 71 0 1
#> 60.1 13.15 1 38 1 0
#> 187.1 9.92 1 39 1 0
#> 107.1 11.18 1 54 1 0
#> 16.1 8.71 1 71 0 1
#> 89 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 189 10.51 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 41 18.02 1 40 1 0
#> 26 15.77 1 49 0 1
#> 97.1 19.14 1 65 0 1
#> 127 3.53 1 62 0 1
#> 10 10.53 1 34 0 0
#> 79.1 16.23 1 54 1 0
#> 129 23.41 1 53 1 0
#> 107.2 11.18 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 57.1 14.46 1 45 0 1
#> 6 15.64 1 39 0 0
#> 149.3 8.37 1 33 1 0
#> 43 12.10 1 61 0 1
#> 26.1 15.77 1 49 0 1
#> 6.1 15.64 1 39 0 0
#> 51.1 18.23 1 83 0 1
#> 111.1 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 4 17.64 1 NA 0 1
#> 188 16.16 1 46 0 1
#> 125.1 15.65 1 67 1 0
#> 30 17.43 1 78 0 0
#> 68.1 20.62 1 44 0 0
#> 40 18.00 1 28 1 0
#> 150.1 20.33 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 127.1 3.53 1 62 0 1
#> 68.2 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 130 16.47 1 53 0 1
#> 114.1 13.68 1 NA 0 0
#> 124.1 9.73 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 124.2 9.73 1 NA 1 0
#> 149.4 8.37 1 33 1 0
#> 184 17.77 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 167.2 15.55 1 56 1 0
#> 96 14.54 1 33 0 1
#> 56 12.21 1 60 0 0
#> 159 10.55 1 50 0 1
#> 167.3 15.55 1 56 1 0
#> 66.1 22.13 1 53 0 0
#> 125.2 15.65 1 67 1 0
#> 52.1 10.42 1 52 0 1
#> 61 10.12 1 36 0 1
#> 59.1 10.16 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 155 13.08 1 26 0 0
#> 5 16.43 1 51 0 1
#> 150.2 20.33 1 48 0 0
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 17 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 122 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 142 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 163 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 17.1 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 31 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 53 24.00 0 32 0 1
#> 74 24.00 0 43 0 1
#> 35.1 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 138.1 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 11 24.00 0 42 0 1
#> 118 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 3 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 162.1 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 17.2 24.00 0 38 0 1
#> 80.1 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 11.1 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 95.1 24.00 0 68 0 1
#> 116.1 24.00 0 58 0 1
#> 172 24.00 0 41 0 0
#> 162.2 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 185.1 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 163.1 24.00 0 66 0 0
#> 144.2 24.00 0 28 0 1
#> 82.1 24.00 0 34 0 0
#> 67 24.00 0 25 0 0
#> 75 24.00 0 21 1 0
#> 67.1 24.00 0 25 0 0
#> 84 24.00 0 39 0 1
#> 115.1 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 53.1 24.00 0 32 0 1
#> 186.2 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 72 24.00 0 40 0 1
#> 144.3 24.00 0 28 0 1
#> 95.2 24.00 0 68 0 1
#> 142.1 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 2 24.00 0 9 0 0
#> 84.1 24.00 0 39 0 1
#> 161 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 163.2 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 102 24.00 0 49 0 0
#> 20.1 24.00 0 46 1 0
#> 182.1 24.00 0 35 0 0
#> 28 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 95.3 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 141.1 24.00 0 44 1 0
#> 72.1 24.00 0 40 0 1
#> 152 24.00 0 36 0 1
#> 72.2 24.00 0 40 0 1
#> 35.2 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.841 NA NA NA
#> 2 age, Cure model 0.0156 NA NA NA
#> 3 grade_ii, Cure model 0.484 NA NA NA
#> 4 grade_iii, Cure model 0.348 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00414 NA NA NA
#> 2 grade_ii, Survival model 0.837 NA NA NA
#> 3 grade_iii, Survival model 0.691 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.8408 0.0156 0.4839 0.3482
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 252.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.84077007 0.01560229 0.48387407 0.34823218
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004144199 0.837147326 0.690855349
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.50388675 0.07810433 0.80661610 0.74366304 0.44056777 0.36152361
#> [7] 0.78302600 0.88211368 0.53376248 0.20438884 0.96634761 0.09189531
#> [13] 0.54365513 0.38465562 0.01341598 0.24422906 0.91845072 0.96634761
#> [19] 0.91845072 0.66155115 0.17483462 0.14608320 0.67024226 0.76727396
#> [25] 0.71119171 0.91845072 0.70295354 0.85214023 0.30446522 0.37305726
#> [31] 0.20438884 0.42943490 0.40681327 0.67024226 0.88952126 0.23111234
#> [37] 0.09189531 0.95270249 0.49361635 0.86715684 0.97989486 0.57266191
#> [43] 0.11841916 0.17483462 0.11841916 0.30446522 0.76727396 0.32727506
#> [49] 0.90404232 0.74366304 0.88952126 0.80661610 0.90404232 0.72762574
#> [55] 0.06256457 0.61825777 0.46210684 0.60032671 0.38465562 0.98664494
#> [61] 0.83696083 0.57266191 0.04325026 0.80661610 0.83696083 0.72762574
#> [67] 0.64412122 0.91845072 0.79877534 0.60032671 0.64412122 0.44056777
#> [73] 0.50388675 0.26901125 0.59111902 0.61825777 0.52370481 0.26901125
#> [79] 0.47276438 0.32727506 0.98664494 0.26901125 0.41809700 0.55342624
#> [85] 0.25691314 0.91845072 0.48317397 0.67024226 0.71944346 0.79089204
#> [91] 0.82935462 0.67024226 0.14608320 0.61825777 0.85214023 0.87465824
#> [97] 0.95270249 0.75937070 0.56309461 0.32727506 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 111 92 107 60 51 158 42 145 106 197 77 113 171
#> 17.45 22.92 11.18 13.15 18.23 20.14 12.43 10.07 16.67 21.60 7.27 22.86 16.57
#> 97 24 36 149 77.1 149.1 39 175 66 167 14 180 149.2
#> 19.14 23.89 21.19 8.37 7.27 8.37 15.59 21.91 22.13 15.55 12.89 14.82 8.37
#> 18 52 128 166 197.1 108 179 167.1 187 153 113.1 70 117
#> 15.21 10.42 20.35 19.98 21.60 18.29 18.63 15.55 9.92 21.33 22.86 7.38 17.46
#> 93 25 79 15 175.1 15.1 128.1 14.1 150 16 60.1 187.1 107.1
#> 10.33 6.32 16.23 22.68 21.91 22.68 20.35 12.89 20.33 8.71 13.15 9.92 11.18
#> 16.1 57 69 125 41 26 97.1 127 10 79.1 129 107.2 10.1
#> 8.71 14.46 23.23 15.65 18.02 15.77 19.14 3.53 10.53 16.23 23.41 11.18 10.53
#> 57.1 6 149.3 43 26.1 6.1 51.1 111.1 68 188 125.1 30 68.1
#> 14.46 15.64 8.37 12.10 15.77 15.64 18.23 17.45 20.62 16.16 15.65 17.43 20.62
#> 40 150.1 127.1 68.2 88 130 32 149.4 184 167.2 96 56 159
#> 18.00 20.33 3.53 20.62 18.37 16.47 20.90 8.37 17.77 15.55 14.54 12.21 10.55
#> 167.3 66.1 125.2 52.1 61 70.1 155 5 150.2 160 174 17 144
#> 15.55 22.13 15.65 10.42 10.12 7.38 13.08 16.43 20.33 24.00 24.00 24.00 24.00
#> 122 82 142 138 186 1 163 35 196 17.1 95 31 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 74 35.1 112 138.1 121 191 11 118 186.1 116 3 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 162.1 121.1 44 17.2 80.1 126 11.1 185 20 95.1 116.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.2 146 185.1 144.1 141 200 163.1 144.2 82.1 67 75 67.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 53.1 186.2 198 72 144.3 95.2 142.1 83 2 84.1 161 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.2 173 182 132 102 20.1 182.1 28 119 95.3 143 174.1 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 152 72.2 35.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[17]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01066196 0.41244009 0.03820652
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.2314988 0.0042034 -0.2398537
#> grade_iii, Cure model
#> 0.9380463
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 24 23.89 1 38 0 0
#> 70 7.38 1 30 1 0
#> 130 16.47 1 53 0 1
#> 16 8.71 1 71 0 1
#> 40 18.00 1 28 1 0
#> 129 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 97 19.14 1 65 0 1
#> 13 14.34 1 54 0 1
#> 107 11.18 1 54 1 0
#> 105 19.75 1 60 0 0
#> 110 17.56 1 65 0 1
#> 180 14.82 1 37 0 0
#> 113 22.86 1 34 0 0
#> 125 15.65 1 67 1 0
#> 175 21.91 1 43 0 0
#> 70.1 7.38 1 30 1 0
#> 13.1 14.34 1 54 0 1
#> 37 12.52 1 57 1 0
#> 189 10.51 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 55 19.34 1 69 0 1
#> 125.1 15.65 1 67 1 0
#> 4 17.64 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 5 16.43 1 51 0 1
#> 43 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 92 22.92 1 47 0 1
#> 79.1 16.23 1 54 1 0
#> 150 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 139 21.49 1 63 1 0
#> 49 12.19 1 48 1 0
#> 60 13.15 1 38 1 0
#> 89.1 11.44 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 91 5.33 1 61 0 1
#> 100 16.07 1 60 0 0
#> 157 15.10 1 47 0 0
#> 92.1 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 13.2 14.34 1 54 0 1
#> 23 16.92 1 61 0 0
#> 117 17.46 1 26 0 1
#> 175.1 21.91 1 43 0 0
#> 154 12.63 1 20 1 0
#> 69.1 23.23 1 25 0 1
#> 125.2 15.65 1 67 1 0
#> 187 9.92 1 39 1 0
#> 10 10.53 1 34 0 0
#> 184 17.77 1 38 0 0
#> 88 18.37 1 47 0 0
#> 57.1 14.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 114 13.68 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 59 10.16 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 4.1 17.64 1 NA 0 1
#> 184.1 17.77 1 38 0 0
#> 29 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 36 21.19 1 48 0 1
#> 4.2 17.64 1 NA 0 1
#> 13.3 14.34 1 54 0 1
#> 89.2 11.44 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 16.1 8.71 1 71 0 1
#> 100.1 16.07 1 60 0 0
#> 63 22.77 1 31 1 0
#> 90 20.94 1 50 0 1
#> 40.1 18.00 1 28 1 0
#> 51 18.23 1 83 0 1
#> 77.1 7.27 1 67 0 1
#> 90.1 20.94 1 50 0 1
#> 188 16.16 1 46 0 1
#> 157.1 15.10 1 47 0 0
#> 96 14.54 1 33 0 1
#> 23.1 16.92 1 61 0 0
#> 127 3.53 1 62 0 1
#> 140 12.68 1 59 1 0
#> 188.1 16.16 1 46 0 1
#> 26 15.77 1 49 0 1
#> 111.1 17.45 1 47 0 1
#> 77.2 7.27 1 67 0 1
#> 190 20.81 1 42 1 0
#> 192 16.44 1 31 1 0
#> 194 22.40 1 38 0 1
#> 128 20.35 1 35 0 1
#> 90.2 20.94 1 50 0 1
#> 113.1 22.86 1 34 0 0
#> 194.1 22.40 1 38 0 1
#> 133 14.65 1 57 0 0
#> 170 19.54 1 43 0 1
#> 155 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 37.1 12.52 1 57 1 0
#> 81 14.06 1 34 0 0
#> 56 12.21 1 60 0 0
#> 58 19.34 1 39 0 0
#> 133.1 14.65 1 57 0 0
#> 29.1 15.45 1 68 1 0
#> 93 10.33 1 52 0 1
#> 128.1 20.35 1 35 0 1
#> 169 22.41 1 46 0 0
#> 56.1 12.21 1 60 0 0
#> 140.1 12.68 1 59 1 0
#> 90.3 20.94 1 50 0 1
#> 38 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 148 24.00 0 61 1 0
#> 176 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 73 24.00 0 NA 0 1
#> 19 24.00 0 57 0 1
#> 98 24.00 0 34 1 0
#> 193 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 122 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 122.1 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 19.1 24.00 0 57 0 1
#> 172 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 87 24.00 0 27 0 0
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 3.2 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 193.1 24.00 0 45 0 1
#> 161 24.00 0 45 0 0
#> 173 24.00 0 19 0 1
#> 138 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 121 24.00 0 57 1 0
#> 148.1 24.00 0 61 1 0
#> 178.1 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 48.1 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 44 24.00 0 56 0 0
#> 174 24.00 0 49 1 0
#> 33 24.00 0 53 0 0
#> 186.1 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 67 24.00 0 25 0 0
#> 7 24.00 0 37 1 0
#> 138.1 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 185 24.00 0 44 1 0
#> 38.1 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 33.1 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 34.1 24.00 0 36 0 0
#> 198 24.00 0 66 0 1
#> 148.2 24.00 0 61 1 0
#> 98.1 24.00 0 34 1 0
#> 33.2 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 165.2 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 94 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 2 24.00 0 9 0 0
#> 163.1 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 7.1 24.00 0 37 1 0
#> 17.1 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 95.1 24.00 0 68 0 1
#> 135.1 24.00 0 58 1 0
#> 121.1 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 20 24.00 0 46 1 0
#> 148.3 24.00 0 61 1 0
#> 84 24.00 0 39 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.231 NA NA NA
#> 2 age, Cure model 0.00420 NA NA NA
#> 3 grade_ii, Cure model -0.240 NA NA NA
#> 4 grade_iii, Cure model 0.938 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0107 NA NA NA
#> 2 grade_ii, Survival model 0.412 NA NA NA
#> 3 grade_iii, Survival model 0.0382 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.231499 0.004203 -0.239854 0.938046
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 248.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.2314988 0.0042034 -0.2398537 0.9380463
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01066196 0.41244009 0.03820652
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.75326693 0.05645349 0.96022512 0.66116521 0.94999356 0.58065573
#> [7] 0.14273632 0.93435313 0.98521313 0.53588309 0.82789791 0.91842418
#> [13] 0.49782672 0.61367727 0.79131903 0.24238398 0.73367659 0.35041487
#> [19] 0.96022512 0.82789791 0.88573825 0.81585006 0.51729525 0.73367659
#> [25] 0.62990996 0.67646468 0.91304484 0.68399935 0.20690158 0.68399935
#> [31] 0.47738939 0.10997918 0.37706658 0.90763391 0.85712686 0.33618413
#> [37] 0.99016657 0.71269879 0.77890079 0.20690158 0.16650035 0.82789791
#> [43] 0.64571082 0.62181326 0.35041487 0.88009235 0.16650035 0.73367659
#> [49] 0.93962634 0.92375091 0.59728047 0.55420105 0.81585006 0.57202517
#> [55] 0.48785670 0.93962634 0.59728047 0.76635240 0.54508553 0.38974395
#> [61] 0.82789791 0.97034031 0.94999356 0.71269879 0.27574453 0.40212606
#> [67] 0.58065573 0.56322007 0.97034031 0.40212606 0.69845175 0.77890079
#> [73] 0.80974229 0.64571082 0.99509558 0.86877384 0.69845175 0.72669517
#> [79] 0.62990996 0.97034031 0.44549342 0.66886316 0.30742054 0.45637988
#> [85] 0.40212606 0.24238398 0.30742054 0.79752905 0.50762101 0.86295663
#> [91] 0.75982492 0.88573825 0.85124650 0.89674595 0.51729525 0.79752905
#> [97] 0.76635240 0.92906425 0.45637988 0.29185432 0.89674595 0.86877384
#> [103] 0.40212606 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 6 24 70 130 16 40 129 61 25 97 13 107 105
#> 15.64 23.89 7.38 16.47 8.71 18.00 23.41 10.12 6.32 19.14 14.34 11.18 19.75
#> 110 180 113 125 175 70.1 13.1 37 57 55 125.1 111 5
#> 17.56 14.82 22.86 15.65 21.91 7.38 14.34 12.52 14.46 19.34 15.65 17.45 16.43
#> 43 79 92 79.1 150 164 139 49 60 66 91 100 157
#> 12.10 16.23 22.92 16.23 20.33 23.60 21.49 12.19 13.15 22.13 5.33 16.07 15.10
#> 92.1 69 13.2 23 117 175.1 154 69.1 125.2 187 10 184 88
#> 22.92 23.23 14.34 16.92 17.46 21.91 12.63 23.23 15.65 9.92 10.53 17.77 18.37
#> 57.1 41 158 187.1 184.1 29 179 36 13.3 77 16.1 100.1 63
#> 14.46 18.02 20.14 9.92 17.77 15.45 18.63 21.19 14.34 7.27 8.71 16.07 22.77
#> 90 40.1 51 77.1 90.1 188 157.1 96 23.1 127 140 188.1 26
#> 20.94 18.00 18.23 7.27 20.94 16.16 15.10 14.54 16.92 3.53 12.68 16.16 15.77
#> 111.1 77.2 190 192 194 128 90.2 113.1 194.1 133 170 155 39
#> 17.45 7.27 20.81 16.44 22.40 20.35 20.94 22.86 22.40 14.65 19.54 13.08 15.59
#> 37.1 81 56 58 133.1 29.1 93 128.1 169 56.1 140.1 90.3 38
#> 12.52 14.06 12.21 19.34 14.65 15.45 10.33 20.35 22.41 12.21 12.68 20.94 24.00
#> 103 148 176 178 19 98 193 3 3.1 165 12 122 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 82 144 122.1 165.1 19.1 172 160 46 48 200 87 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 3.2 147 193.1 161 173 138 147.1 121 148.1 178.1 152 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 186 48.1 116 44 174 33 186.1 54 67 7 138.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 185 38.1 27.1 1 33.1 104 34.1 198 148.2 98.1 33.2 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 135 165.2 83 94 182 2 163.1 95 132 7.1 17.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 135.1 121.1 74 20 148.3 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[18]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01019387 0.82991395 0.13453887
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.217539e+00 2.346543e-02 -2.841966e-05
#> grade_iii, Cure model
#> 1.077022e+00
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 45 17.42 1 54 0 1
#> 106 16.67 1 49 1 0
#> 49 12.19 1 48 1 0
#> 10 10.53 1 34 0 0
#> 99 21.19 1 38 0 1
#> 15 22.68 1 48 0 0
#> 169 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 97 19.14 1 65 0 1
#> 188 16.16 1 46 0 1
#> 175 21.91 1 43 0 0
#> 55 19.34 1 69 0 1
#> 6 15.64 1 39 0 0
#> 181 16.46 1 45 0 1
#> 6.1 15.64 1 39 0 0
#> 168 23.72 1 70 0 0
#> 123 13.00 1 44 1 0
#> 128 20.35 1 35 0 1
#> 4 17.64 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 43 12.10 1 61 0 1
#> 159 10.55 1 50 0 1
#> 76 19.22 1 54 0 1
#> 149 8.37 1 33 1 0
#> 166 19.98 1 48 0 0
#> 41 18.02 1 40 1 0
#> 45.1 17.42 1 54 0 1
#> 101.1 9.97 1 10 0 1
#> 158 20.14 1 74 1 0
#> 145 10.07 1 65 1 0
#> 18 15.21 1 49 1 0
#> 29 15.45 1 68 1 0
#> 171 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 134 17.81 1 47 1 0
#> 170 19.54 1 43 0 1
#> 190 20.81 1 42 1 0
#> 92 22.92 1 47 0 1
#> 15.1 22.68 1 48 0 0
#> 145.1 10.07 1 65 1 0
#> 167 15.55 1 56 1 0
#> 136 21.83 1 43 0 1
#> 6.2 15.64 1 39 0 0
#> 41.1 18.02 1 40 1 0
#> 49.1 12.19 1 48 1 0
#> 105 19.75 1 60 0 0
#> 60 13.15 1 38 1 0
#> 177 12.53 1 75 0 0
#> 97.1 19.14 1 65 0 1
#> 99.1 21.19 1 38 0 1
#> 86 23.81 1 58 0 1
#> 89 11.44 1 NA 0 0
#> 187 9.92 1 39 1 0
#> 167.1 15.55 1 56 1 0
#> 56 12.21 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 58 19.34 1 39 0 0
#> 175.1 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 43.1 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 32 20.90 1 37 1 0
#> 97.2 19.14 1 65 0 1
#> 166.1 19.98 1 48 0 0
#> 57 14.46 1 45 0 1
#> 96.1 14.54 1 33 0 1
#> 183 9.24 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 168.1 23.72 1 70 0 0
#> 99.2 21.19 1 38 0 1
#> 105.2 19.75 1 60 0 0
#> 60.1 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 171.1 16.57 1 41 0 1
#> 154 12.63 1 20 1 0
#> 167.2 15.55 1 56 1 0
#> 192 16.44 1 31 1 0
#> 101.2 9.97 1 10 0 1
#> 114 13.68 1 NA 0 0
#> 170.1 19.54 1 43 0 1
#> 170.2 19.54 1 43 0 1
#> 125 15.65 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 155.1 13.08 1 26 0 0
#> 194 22.40 1 38 0 1
#> 101.3 9.97 1 10 0 1
#> 127.1 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 97.3 19.14 1 65 0 1
#> 29.1 15.45 1 68 1 0
#> 181.1 16.46 1 45 0 1
#> 157.1 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 56.1 12.21 1 60 0 0
#> 100 16.07 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 159.2 10.55 1 50 0 1
#> 111 17.45 1 47 0 1
#> 192.1 16.44 1 31 1 0
#> 155.2 13.08 1 26 0 0
#> 150 20.33 1 48 0 0
#> 89.1 11.44 1 NA 0 0
#> 26 15.77 1 49 0 1
#> 170.3 19.54 1 43 0 1
#> 179.1 18.63 1 42 0 0
#> 194.1 22.40 1 38 0 1
#> 42 12.43 1 49 0 1
#> 52 10.42 1 52 0 1
#> 10.1 10.53 1 34 0 0
#> 8 18.43 1 32 0 0
#> 165 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 48 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 173.1 24.00 0 19 0 1
#> 103 24.00 0 56 1 0
#> 20 24.00 0 46 1 0
#> 72 24.00 0 40 0 1
#> 174 24.00 0 49 1 0
#> 71.1 24.00 0 51 0 0
#> 173.2 24.00 0 19 0 1
#> 144 24.00 0 28 0 1
#> 84 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 103.1 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 9 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 173.3 24.00 0 19 0 1
#> 104 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 178 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 74.1 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 186 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 162 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 82 24.00 0 34 0 0
#> 193.1 24.00 0 45 0 1
#> 163.1 24.00 0 66 0 0
#> 160.1 24.00 0 31 1 0
#> 193.2 24.00 0 45 0 1
#> 33.1 24.00 0 53 0 0
#> 172.1 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 75 24.00 0 21 1 0
#> 161 24.00 0 45 0 0
#> 126.1 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 19 24.00 0 57 0 1
#> 22.1 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 186.1 24.00 0 45 1 0
#> 1.1 24.00 0 23 1 0
#> 2 24.00 0 9 0 0
#> 87 24.00 0 27 0 0
#> 131 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 144.1 24.00 0 28 0 1
#> 48.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 165.1 24.00 0 47 0 0
#> 9.1 24.00 0 31 1 0
#> 165.2 24.00 0 47 0 0
#> 64.1 24.00 0 43 0 0
#> 161.1 24.00 0 45 0 0
#> 174.1 24.00 0 49 1 0
#> 82.1 24.00 0 34 0 0
#> 115 24.00 0 NA 1 0
#> 9.2 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 104.1 24.00 0 50 1 0
#> 160.2 24.00 0 31 1 0
#> 82.2 24.00 0 34 0 0
#> 131.1 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 75.1 24.00 0 21 1 0
#> 46 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 83 24.00 0 6 0 0
#> 94 24.00 0 51 0 1
#> 122 24.00 0 66 0 0
#> 193.3 24.00 0 45 0 1
#> 67 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.22 NA NA NA
#> 2 age, Cure model 0.0235 NA NA NA
#> 3 grade_ii, Cure model -0.0000284 NA NA NA
#> 4 grade_iii, Cure model 1.08 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0102 NA NA NA
#> 2 grade_ii, Survival model 0.830 NA NA NA
#> 3 grade_iii, Survival model 0.135 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.218e+00 2.347e-02 -2.842e-05 1.077e+00
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 250.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.217539e+00 2.346543e-02 -2.841966e-05 1.077022e+00
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01019387 0.82991395 0.13453887
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.682373470 0.368608280 0.389506420 0.776556002 0.850346725 0.072079250
#> [7] 0.019258113 0.030233460 0.904211472 0.246266919 0.473112648 0.049848794
#> [13] 0.208770772 0.515121883 0.420944019 0.515121883 0.002735736 0.713628053
#> [19] 0.110184774 0.608972783 0.797436138 0.818529323 0.227255462 0.968052746
#> [25] 0.133587586 0.327331941 0.368608280 0.904211472 0.125745974 0.882714295
#> [31] 0.598558974 0.577772189 0.399987948 0.629892391 0.347899812 0.174540290
#> [37] 0.102609000 0.014100960 0.019258113 0.882714295 0.546712074 0.064202747
#> [43] 0.515121883 0.327331941 0.776556002 0.149514038 0.661598119 0.734500884
#> [49] 0.246266919 0.072079250 0.000564134 0.946629078 0.546712074 0.755445572
#> [55] 0.149514038 0.208770772 0.049848794 0.978680131 0.797436138 0.462778055
#> [61] 0.094746601 0.246266919 0.133587586 0.650939825 0.629892391 0.957350396
#> [67] 0.227255462 0.002735736 0.072079250 0.149514038 0.661598119 0.009451850
#> [73] 0.399987948 0.724129907 0.546712074 0.442193152 0.904211472 0.174540290
#> [79] 0.174540290 0.504585568 0.682373470 0.036839613 0.904211472 0.978680131
#> [85] 0.316518765 0.246266919 0.577772189 0.420944019 0.608972783 0.285199763
#> [91] 0.755445572 0.483511809 0.818529323 0.818529323 0.358210421 0.442193152
#> [97] 0.682373470 0.117865962 0.494014325 0.174540290 0.285199763 0.036839613
#> [103] 0.744950719 0.871850990 0.850346725 0.305890464 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 155 45 106 49 10 99 15 169 101 97 188 175 55
#> 13.08 17.42 16.67 12.19 10.53 21.19 22.68 22.41 9.97 19.14 16.16 21.91 19.34
#> 6 181 6.1 168 123 128 157 43 159 76 149 166 41
#> 15.64 16.46 15.64 23.72 13.00 20.35 15.10 12.10 10.55 19.22 8.37 19.98 18.02
#> 45.1 101.1 158 145 18 29 171 96 134 170 190 92 15.1
#> 17.42 9.97 20.14 10.07 15.21 15.45 16.57 14.54 17.81 19.54 20.81 22.92 22.68
#> 145.1 167 136 6.2 41.1 49.1 105 60 177 97.1 99.1 86 187
#> 10.07 15.55 21.83 15.64 18.02 12.19 19.75 13.15 12.53 19.14 21.19 23.81 9.92
#> 167.1 56 105.1 58 175.1 127 43.1 79 32 97.2 166.1 57 96.1
#> 15.55 12.21 19.75 19.34 21.91 3.53 12.10 16.23 20.90 19.14 19.98 14.46 14.54
#> 183 76.1 168.1 99.2 105.2 60.1 69 171.1 154 167.2 192 101.2 170.1
#> 9.24 19.22 23.72 21.19 19.75 13.15 23.23 16.57 12.63 15.55 16.44 9.97 19.54
#> 170.2 125 155.1 194 101.3 127.1 51 97.3 29.1 181.1 157.1 179 56.1
#> 19.54 15.65 13.08 22.40 9.97 3.53 18.23 19.14 15.45 16.46 15.10 18.63 12.21
#> 100 159.1 159.2 111 192.1 155.2 150 26 170.3 179.1 194.1 42 52
#> 16.07 10.55 10.55 17.45 16.44 13.08 20.33 15.77 19.54 18.63 22.40 12.43 10.42
#> 10.1 8 165 7 173 48 71 33 160 44 173.1 103 20
#> 10.53 18.43 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 174 71.1 173.2 144 84 74 103.1 172 193 147 9 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 173.3 104 1 178 17 74.1 28 186 163 53 162 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 193.1 163.1 160.1 193.2 33.1 172.1 116 75 161 126.1 112 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 19 22.1 146 186.1 1.1 2 87 131 65 144.1 48.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 165.1 9.1 165.2 64.1 161.1 174.1 82.1 9.2 80 104.1 160.2 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 34 75.1 46 27 83 94 122 193.3 67 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[19]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003346469 0.873796963 0.524594689
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.13652443 0.01757039 0.31481261
#> grade_iii, Cure model
#> 1.10130103
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 32 20.90 1 37 1 0
#> 168 23.72 1 70 0 0
#> 124 9.73 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 40 18.00 1 28 1 0
#> 18 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 158 20.14 1 74 1 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 124.1 9.73 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 81 14.06 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 159 10.55 1 50 0 1
#> 15 22.68 1 48 0 0
#> 69 23.23 1 25 0 1
#> 114 13.68 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 61 10.12 1 36 0 1
#> 24 23.89 1 38 0 0
#> 41 18.02 1 40 1 0
#> 30 17.43 1 78 0 0
#> 30.1 17.43 1 78 0 0
#> 177 12.53 1 75 0 0
#> 199.1 19.81 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 187 9.92 1 39 1 0
#> 50 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 69.1 23.23 1 25 0 1
#> 139 21.49 1 63 1 0
#> 97.2 19.14 1 65 0 1
#> 59 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 106 16.67 1 49 1 0
#> 29 15.45 1 68 1 0
#> 58 19.34 1 39 0 0
#> 164 23.60 1 76 0 1
#> 40.1 18.00 1 28 1 0
#> 5 16.43 1 51 0 1
#> 60 13.15 1 38 1 0
#> 16.1 8.71 1 71 0 1
#> 76 19.22 1 54 0 1
#> 127 3.53 1 62 0 1
#> 168.1 23.72 1 70 0 0
#> 171 16.57 1 41 0 1
#> 45 17.42 1 54 0 1
#> 128.1 20.35 1 35 0 1
#> 25 6.32 1 34 1 0
#> 29.1 15.45 1 68 1 0
#> 90.1 20.94 1 50 0 1
#> 128.2 20.35 1 35 0 1
#> 37 12.52 1 57 1 0
#> 145 10.07 1 65 1 0
#> 57 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 180 14.82 1 37 0 0
#> 145.1 10.07 1 65 1 0
#> 158.1 20.14 1 74 1 0
#> 41.1 18.02 1 40 1 0
#> 86 23.81 1 58 0 1
#> 43 12.10 1 61 0 1
#> 158.2 20.14 1 74 1 0
#> 107 11.18 1 54 1 0
#> 18.1 15.21 1 49 1 0
#> 16.2 8.71 1 71 0 1
#> 157 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 124.2 9.73 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 167 15.55 1 56 1 0
#> 43.1 12.10 1 61 0 1
#> 50.1 10.02 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 168.2 23.72 1 70 0 0
#> 171.1 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 40.2 18.00 1 28 1 0
#> 183 9.24 1 67 1 0
#> 78 23.88 1 43 0 0
#> 114.1 13.68 1 NA 0 0
#> 134 17.81 1 47 1 0
#> 49 12.19 1 48 1 0
#> 133 14.65 1 57 0 0
#> 5.1 16.43 1 51 0 1
#> 99 21.19 1 38 0 1
#> 40.3 18.00 1 28 1 0
#> 18.2 15.21 1 49 1 0
#> 114.2 13.68 1 NA 0 0
#> 93 10.33 1 52 0 1
#> 197 21.60 1 69 1 0
#> 184.1 17.77 1 38 0 0
#> 153 21.33 1 55 1 0
#> 157.1 15.10 1 47 0 0
#> 79 16.23 1 54 1 0
#> 49.1 12.19 1 48 1 0
#> 111.1 17.45 1 47 0 1
#> 14 12.89 1 21 0 0
#> 23 16.92 1 61 0 0
#> 136.1 21.83 1 43 0 1
#> 23.1 16.92 1 61 0 0
#> 68.1 20.62 1 44 0 0
#> 188 16.16 1 46 0 1
#> 170 19.54 1 43 0 1
#> 97.3 19.14 1 65 0 1
#> 78.1 23.88 1 43 0 0
#> 88 18.37 1 47 0 0
#> 78.2 23.88 1 43 0 0
#> 171.2 16.57 1 41 0 1
#> 14.1 12.89 1 21 0 0
#> 141 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 151 24.00 0 42 0 0
#> 144 24.00 0 28 0 1
#> 28 24.00 0 67 1 0
#> 2 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 84 24.00 0 39 0 1
#> 22 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 135 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#> 135.1 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 161.1 24.00 0 45 0 0
#> 46 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 138 24.00 0 44 1 0
#> 135.2 24.00 0 58 1 0
#> 152 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 132 24.00 0 55 0 0
#> 35 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 35.1 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 11 24.00 0 42 0 1
#> 112 24.00 0 61 0 0
#> 138.1 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 2.1 24.00 0 9 0 0
#> 178 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 118.1 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 144.1 24.00 0 28 0 1
#> 121 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 132.1 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 95.1 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 104 24.00 0 50 1 0
#> 98 24.00 0 34 1 0
#> 33.1 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 33.2 24.00 0 53 0 0
#> 121.1 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 144.2 24.00 0 28 0 1
#> 143.1 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 82.1 24.00 0 34 0 0
#> 176 24.00 0 43 0 1
#> 193.1 24.00 0 45 0 1
#> 83 24.00 0 6 0 0
#> 121.2 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 163 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 20.1 24.00 0 46 1 0
#> 102.2 24.00 0 49 0 0
#> 138.2 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 126 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 196 24.00 0 19 0 0
#> 98.1 24.00 0 34 1 0
#> 163.1 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 144.3 24.00 0 28 0 1
#> 11.1 24.00 0 42 0 1
#> 135.3 24.00 0 58 1 0
#> 162 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.14 NA NA NA
#> 2 age, Cure model 0.0176 NA NA NA
#> 3 grade_ii, Cure model 0.315 NA NA NA
#> 4 grade_iii, Cure model 1.10 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00335 NA NA NA
#> 2 grade_ii, Survival model 0.874 NA NA NA
#> 3 grade_iii, Survival model 0.525 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.13652 0.01757 0.31481 1.10130
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 249.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.13652443 0.01757039 0.31481261 1.10130103
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003346469 0.873796963 0.524594689
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.45384332 0.18850363 0.49794310 0.64710643 0.82240246 0.47633737
#> [7] 0.52824376 0.58226045 0.58226045 0.89130976 0.86858504 0.97078218
#> [13] 0.93484796 0.30745224 0.27194469 0.98544807 0.94534910 0.03502295
#> [19] 0.63138347 0.71130389 0.71130389 0.89692534 0.34351963 0.96072944
#> [25] 0.43014919 0.27194469 0.39039664 0.58226045 0.69733877 0.74578650
#> [31] 0.81035774 0.56436824 0.25123184 0.64710643 0.77216772 0.87432613
#> [37] 0.97078218 0.57338583 0.99517967 0.18850363 0.75255021 0.72518771
#> [43] 0.49794310 0.99033401 0.81035774 0.43014919 0.49794310 0.90253091
#> [49] 0.95055871 0.86283937 0.46532911 0.85126555 0.95055871 0.52824376
#> [55] 0.63138347 0.16219164 0.91887928 0.52824376 0.92955282 0.82240246
#> [61] 0.97078218 0.83971258 0.61482169 0.68309482 0.80412613 0.91887928
#> [67] 0.32556309 0.18850363 0.75255021 0.79780190 0.64710643 0.96578194
#> [73] 0.08448645 0.67591492 0.90807111 0.85705656 0.77216772 0.41742551
#> [79] 0.64710643 0.82240246 0.94011335 0.37541038 0.68309482 0.40433524
#> [85] 0.83971258 0.78508149 0.90807111 0.69733877 0.88000308 0.73209511
#> [91] 0.34351963 0.73209511 0.47633737 0.79146651 0.55533053 0.58226045
#> [97] 0.08448645 0.62311195 0.08448645 0.75255021 0.88000308 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 32 168 128 40 18 68 158 97 97.1 154 81 16 159
#> 20.90 23.72 20.35 18.00 15.21 20.62 20.14 19.14 19.14 12.63 14.06 8.71 10.55
#> 15 69 77 61 24 41 30 30.1 177 136 187 90 69.1
#> 22.68 23.23 7.27 10.12 23.89 18.02 17.43 17.43 12.53 21.83 9.92 20.94 23.23
#> 139 97.2 111 106 29 58 164 40.1 5 60 16.1 76 127
#> 21.49 19.14 17.45 16.67 15.45 19.34 23.60 18.00 16.43 13.15 8.71 19.22 3.53
#> 168.1 171 45 128.1 25 29.1 90.1 128.2 37 145 57 190 180
#> 23.72 16.57 17.42 20.35 6.32 15.45 20.94 20.35 12.52 10.07 14.46 20.81 14.82
#> 145.1 158.1 41.1 86 43 158.2 107 18.1 16.2 157 179 184 167
#> 10.07 20.14 18.02 23.81 12.10 20.14 11.18 15.21 8.71 15.10 18.63 17.77 15.55
#> 43.1 175 168.2 171.1 100 40.2 183 78 134 49 133 5.1 99
#> 12.10 21.91 23.72 16.57 16.07 18.00 9.24 23.88 17.81 12.19 14.65 16.43 21.19
#> 40.3 18.2 93 197 184.1 153 157.1 79 49.1 111.1 14 23 136.1
#> 18.00 15.21 10.33 21.60 17.77 21.33 15.10 16.23 12.19 17.45 12.89 16.92 21.83
#> 23.1 68.1 188 170 97.3 78.1 88 78.2 171.2 14.1 141 102 151
#> 16.92 20.62 16.16 19.54 19.14 23.88 18.37 23.88 16.57 12.89 24.00 24.00 24.00
#> 144 28 2 21 161 84 22 82 135 156 135.1 142 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 151.1 138 135.2 152 9 102.1 116 132 35 65 35.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 11 112 138.1 95 143 27 2.1 178 20 118.1 27.1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 144.1 121 33 132.1 131 131.1 95.1 174 104 98 33.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 33.2 121.1 47 122 144.2 143.1 80 82.1 176 193.1 83 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 64 163 34 20.1 102.2 138.2 119 126 160 21.1 196 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 47.1 144.3 11.1 135.3 162 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[20]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003422178 0.323525286 0.358228954
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.053153480 -0.005299494 0.720791617
#> grade_iii, Cure model
#> 0.568663619
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 68 20.62 1 44 0 0
#> 24 23.89 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 66 22.13 1 53 0 0
#> 40 18.00 1 28 1 0
#> 96 14.54 1 33 0 1
#> 154 12.63 1 20 1 0
#> 100 16.07 1 60 0 0
#> 36 21.19 1 48 0 1
#> 134 17.81 1 47 1 0
#> 170 19.54 1 43 0 1
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 108 18.29 1 39 0 1
#> 59 10.16 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 110 17.56 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 40.1 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 101 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 15 22.68 1 48 0 0
#> 92 22.92 1 47 0 1
#> 56 12.21 1 60 0 0
#> 167 15.55 1 56 1 0
#> 123 13.00 1 44 1 0
#> 5 16.43 1 51 0 1
#> 92.1 22.92 1 47 0 1
#> 175 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 166 19.98 1 48 0 0
#> 61 10.12 1 36 0 1
#> 6 15.64 1 39 0 0
#> 99 21.19 1 38 0 1
#> 86 23.81 1 58 0 1
#> 187 9.92 1 39 1 0
#> 88 18.37 1 47 0 0
#> 42 12.43 1 49 0 1
#> 97 19.14 1 65 0 1
#> 26.1 15.77 1 49 0 1
#> 49 12.19 1 48 1 0
#> 149 8.37 1 33 1 0
#> 99.1 21.19 1 38 0 1
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 108.1 18.29 1 39 0 1
#> 129 23.41 1 53 1 0
#> 25 6.32 1 34 1 0
#> 107 11.18 1 54 1 0
#> 49.1 12.19 1 48 1 0
#> 168.1 23.72 1 70 0 0
#> 57 14.46 1 45 0 1
#> 117 17.46 1 26 0 1
#> 194 22.40 1 38 0 1
#> 93 10.33 1 52 0 1
#> 194.1 22.40 1 38 0 1
#> 181.1 16.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 129.1 23.41 1 53 1 0
#> 195 11.76 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 159 10.55 1 50 0 1
#> 10 10.53 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 81.1 14.06 1 34 0 0
#> 134.1 17.81 1 47 1 0
#> 100.1 16.07 1 60 0 0
#> 30 17.43 1 78 0 0
#> 159.1 10.55 1 50 0 1
#> 123.1 13.00 1 44 1 0
#> 68.1 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 128 20.35 1 35 0 1
#> 63 22.77 1 31 1 0
#> 180 14.82 1 37 0 0
#> 96.1 14.54 1 33 0 1
#> 90 20.94 1 50 0 1
#> 129.2 23.41 1 53 1 0
#> 32 20.90 1 37 1 0
#> 93.1 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 58.1 19.34 1 39 0 0
#> 88.1 18.37 1 47 0 0
#> 26.2 15.77 1 49 0 1
#> 41 18.02 1 40 1 0
#> 88.2 18.37 1 47 0 0
#> 110.1 17.56 1 65 0 1
#> 190 20.81 1 42 1 0
#> 16.1 8.71 1 71 0 1
#> 133 14.65 1 57 0 0
#> 189 10.51 1 NA 1 0
#> 49.2 12.19 1 48 1 0
#> 188 16.16 1 46 0 1
#> 97.1 19.14 1 65 0 1
#> 140 12.68 1 59 1 0
#> 63.1 22.77 1 31 1 0
#> 68.2 20.62 1 44 0 0
#> 117.1 17.46 1 26 0 1
#> 91 5.33 1 61 0 1
#> 49.3 12.19 1 48 1 0
#> 32.1 20.90 1 37 1 0
#> 123.2 13.00 1 44 1 0
#> 37 12.52 1 57 1 0
#> 15.1 22.68 1 48 0 0
#> 41.1 18.02 1 40 1 0
#> 99.2 21.19 1 38 0 1
#> 77 7.27 1 67 0 1
#> 32.2 20.90 1 37 1 0
#> 9 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 144 24.00 0 28 0 1
#> 160 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 178 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 95 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 173 24.00 0 19 0 1
#> 161 24.00 0 45 0 0
#> 144.1 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 162 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 161.1 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 53.1 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 193.1 24.00 0 45 0 1
#> 135 24.00 0 58 1 0
#> 64 24.00 0 43 0 0
#> 142 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 176 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 163 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 7 24.00 0 37 1 0
#> 142.1 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 131 24.00 0 66 0 0
#> 144.2 24.00 0 28 0 1
#> 173.1 24.00 0 19 0 1
#> 161.2 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 162.1 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 162.2 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 162.3 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 53.2 24.00 0 32 0 1
#> 198.1 24.00 0 66 0 1
#> 119 24.00 0 17 0 0
#> 152 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 46 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 193.2 24.00 0 45 0 1
#> 173.2 24.00 0 19 0 1
#> 146 24.00 0 63 1 0
#> 53.3 24.00 0 32 0 1
#> 182.1 24.00 0 35 0 0
#> 73 24.00 0 NA 0 1
#> 46.1 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 46.2 24.00 0 71 0 0
#> 131.1 24.00 0 66 0 0
#> 9.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 17.1 24.00 0 38 0 1
#> 71 24.00 0 51 0 0
#> 198.2 24.00 0 66 0 1
#> 191 24.00 0 60 0 1
#> 28.1 24.00 0 67 1 0
#> 174 24.00 0 49 1 0
#> 141 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 142.2 24.00 0 53 0 0
#> 196 24.00 0 19 0 0
#> 152.1 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 46.3 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 132.1 24.00 0 55 0 0
#> 54 24.00 0 53 1 0
#> 38 24.00 0 31 1 0
#> 152.2 24.00 0 36 0 1
#> 46.4 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0532 NA NA NA
#> 2 age, Cure model -0.00530 NA NA NA
#> 3 grade_ii, Cure model 0.721 NA NA NA
#> 4 grade_iii, Cure model 0.569 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00342 NA NA NA
#> 2 grade_ii, Survival model 0.324 NA NA NA
#> 3 grade_iii, Survival model 0.358 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.053153 -0.005299 0.720792 0.568664
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 260.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.053153480 -0.005299494 0.720791617 0.568663619
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003422178 0.323525286 0.358228954
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.298534638 0.006800756 0.584189111 0.174966639 0.494019197 0.708319745
#> [7] 0.787017745 0.628789075 0.206757657 0.512222555 0.363925743 0.419962215
#> [13] 0.196188250 0.457119641 0.646558833 0.530312419 0.734688716 0.494019197
#> [19] 0.575147696 0.932595405 0.034584807 0.133659961 0.091709414 0.821676406
#> [25] 0.681683451 0.752247675 0.602008054 0.091709414 0.185535855 0.335575419
#> [31] 0.354456446 0.924084763 0.672804118 0.206757657 0.021240524 0.941076432
#> [37] 0.429337737 0.813009234 0.401462846 0.646558833 0.830360581 0.966359684
#> [43] 0.206757657 0.949541491 0.373337506 0.457119641 0.060045590 0.983207142
#> [49] 0.872917732 0.830360581 0.034584807 0.725879418 0.548313047 0.154664064
#> [55] 0.907100610 0.154664064 0.584189111 0.610957542 0.060045590 0.392040266
#> [61] 0.881507902 0.898536585 0.787017745 0.734688716 0.512222555 0.628789075
#> [67] 0.566132983 0.881507902 0.752247675 0.298534638 0.864314965 0.206757657
#> [73] 0.326165665 0.113149638 0.690546511 0.708319745 0.252025731 0.060045590
#> [79] 0.261732652 0.907100610 0.345025328 0.373337506 0.429337737 0.646558833
#> [85] 0.475642786 0.429337737 0.530312419 0.289150556 0.949541491 0.699423123
#> [91] 0.830360581 0.619887566 0.401462846 0.778260963 0.113149638 0.298534638
#> [97] 0.548313047 0.991609302 0.830360581 0.261732652 0.752247675 0.804322625
#> [103] 0.133659961 0.475642786 0.206757657 0.974788422 0.261732652 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 68 24 181 66 40 96 154 100 36 134 170 8 153
#> 20.62 23.89 16.46 22.13 18.00 14.54 12.63 16.07 21.19 17.81 19.54 18.43 21.33
#> 108 26 110 81 40.1 23 101 168 15 92 56 167 123
#> 18.29 15.77 17.56 14.06 18.00 16.92 9.97 23.72 22.68 22.92 12.21 15.55 13.00
#> 5 92.1 175 150 166 61 6 99 86 187 88 42 97
#> 16.43 22.92 21.91 20.33 19.98 10.12 15.64 21.19 23.81 9.92 18.37 12.43 19.14
#> 26.1 49 149 99.1 16 58 108.1 129 25 107 49.1 168.1 57
#> 15.77 12.19 8.37 21.19 8.71 19.34 18.29 23.41 6.32 11.18 12.19 23.72 14.46
#> 117 194 93 194.1 181.1 79 129.1 76 159 10 154.1 81.1 134.1
#> 17.46 22.40 10.33 22.40 16.46 16.23 23.41 19.22 10.55 10.53 12.63 14.06 17.81
#> 100.1 30 159.1 123.1 68.1 43 36.1 128 63 180 96.1 90 129.2
#> 16.07 17.43 10.55 13.00 20.62 12.10 21.19 20.35 22.77 14.82 14.54 20.94 23.41
#> 32 93.1 158 58.1 88.1 26.2 41 88.2 110.1 190 16.1 133 49.2
#> 20.90 10.33 20.14 19.34 18.37 15.77 18.02 18.37 17.56 20.81 8.71 14.65 12.19
#> 188 97.1 140 63.1 68.2 117.1 91 49.3 32.1 123.2 37 15.1 41.1
#> 16.16 19.14 12.68 22.77 20.62 17.46 5.33 12.19 20.90 13.00 12.52 22.68 18.02
#> 99.2 77 32.2 9 148 144 160 193 178 19 95 143 28
#> 21.19 7.27 20.90 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 173 161 144.1 53 162 165 161.1 21 94 53.1 122 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 64 142 182 176 198 163 112 7 142.1 131 144.2 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.2 156 103 162.1 112.1 185 162.2 17 162.3 172 53.2 198.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 200 46 22 193.2 173.2 146 53.3 182.1 46.1 74 46.2 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 65 116 17.1 71 198.2 191 28.1 174 141 84 142.2 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 151 47 46.3 132 132.1 54 38 152.2 46.4 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[21]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0008956884 0.5529223532 0.1669781861
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.548946427 0.008775645 0.083160741
#> grade_iii, Cure model
#> 0.853719460
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 70 7.38 1 30 1 0
#> 15 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 43 12.10 1 61 0 1
#> 158 20.14 1 74 1 0
#> 136 21.83 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 117 17.46 1 26 0 1
#> 108 18.29 1 39 0 1
#> 100 16.07 1 60 0 0
#> 8 18.43 1 32 0 0
#> 50 10.02 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 58 19.34 1 39 0 0
#> 106 16.67 1 49 1 0
#> 66 22.13 1 53 0 0
#> 153 21.33 1 55 1 0
#> 124 9.73 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 114 13.68 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 32 20.90 1 37 1 0
#> 13 14.34 1 54 0 1
#> 85 16.44 1 36 0 0
#> 180 14.82 1 37 0 0
#> 8.1 18.43 1 32 0 0
#> 32.1 20.90 1 37 1 0
#> 167 15.55 1 56 1 0
#> 157 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 107 11.18 1 54 1 0
#> 164.1 23.60 1 76 0 1
#> 167.1 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 177.1 12.53 1 75 0 0
#> 42.1 12.43 1 49 0 1
#> 113 22.86 1 34 0 0
#> 23 16.92 1 61 0 0
#> 18.1 15.21 1 49 1 0
#> 78 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 192 16.44 1 31 1 0
#> 133 14.65 1 57 0 0
#> 110 17.56 1 65 0 1
#> 16 8.71 1 71 0 1
#> 81 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 50.1 10.02 1 NA 1 0
#> 50.2 10.02 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 60.1 13.15 1 38 1 0
#> 129 23.41 1 53 1 0
#> 106.1 16.67 1 49 1 0
#> 194 22.40 1 38 0 1
#> 111 17.45 1 47 0 1
#> 175 21.91 1 43 0 0
#> 89 11.44 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 128 20.35 1 35 0 1
#> 58.1 19.34 1 39 0 0
#> 114.1 13.68 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 96 14.54 1 33 0 1
#> 8.2 18.43 1 32 0 0
#> 128.1 20.35 1 35 0 1
#> 167.2 15.55 1 56 1 0
#> 157.1 15.10 1 47 0 0
#> 55.1 19.34 1 69 0 1
#> 89.1 11.44 1 NA 0 0
#> 105 19.75 1 60 0 0
#> 63 22.77 1 31 1 0
#> 140 12.68 1 59 1 0
#> 89.2 11.44 1 NA 0 0
#> 179.1 18.63 1 42 0 0
#> 90 20.94 1 50 0 1
#> 50.3 10.02 1 NA 1 0
#> 179.2 18.63 1 42 0 0
#> 18.2 15.21 1 49 1 0
#> 90.1 20.94 1 50 0 1
#> 68 20.62 1 44 0 0
#> 158.1 20.14 1 74 1 0
#> 69.1 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 15.1 22.68 1 48 0 0
#> 188 16.16 1 46 0 1
#> 16.1 8.71 1 71 0 1
#> 124.1 9.73 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 29 15.45 1 68 1 0
#> 70.1 7.38 1 30 1 0
#> 133.1 14.65 1 57 0 0
#> 107.1 11.18 1 54 1 0
#> 51.1 18.23 1 83 0 1
#> 43.1 12.10 1 61 0 1
#> 105.1 19.75 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 159 10.55 1 50 0 1
#> 70.2 7.38 1 30 1 0
#> 168 23.72 1 70 0 0
#> 175.1 21.91 1 43 0 0
#> 170.1 19.54 1 43 0 1
#> 133.2 14.65 1 57 0 0
#> 55.2 19.34 1 69 0 1
#> 29.1 15.45 1 68 1 0
#> 123 13.00 1 44 1 0
#> 197 21.60 1 69 1 0
#> 181 16.46 1 45 0 1
#> 109 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#> 148 24.00 0 61 1 0
#> 94 24.00 0 51 0 1
#> 118 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 22 24.00 0 52 1 0
#> 98.1 24.00 0 34 1 0
#> 21 24.00 0 47 0 0
#> 19 24.00 0 57 0 1
#> 64 24.00 0 43 0 0
#> 119 24.00 0 17 0 0
#> 137 24.00 0 45 1 0
#> 94.1 24.00 0 51 0 1
#> 47.1 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 151.1 24.00 0 42 0 0
#> 120 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 186 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 109.1 24.00 0 48 0 0
#> 121 24.00 0 57 1 0
#> 151.2 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 74 24.00 0 43 0 1
#> 64.1 24.00 0 43 0 0
#> 196 24.00 0 19 0 0
#> 148.1 24.00 0 61 1 0
#> 11 24.00 0 42 0 1
#> 20 24.00 0 46 1 0
#> 82 24.00 0 34 0 0
#> 46.1 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 172.1 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 31 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 186.1 24.00 0 45 1 0
#> 62.1 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 198 24.00 0 66 0 1
#> 44 24.00 0 56 0 0
#> 74.1 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 2.1 24.00 0 9 0 0
#> 98.2 24.00 0 34 1 0
#> 147.1 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 65 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 198.1 24.00 0 66 0 1
#> 46.2 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 196.1 24.00 0 19 0 0
#> 73 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 65.1 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 198.2 24.00 0 66 0 1
#> 126 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 64.2 24.00 0 43 0 0
#> 143 24.00 0 51 0 0
#> 148.2 24.00 0 61 1 0
#> 176 24.00 0 43 0 1
#> 131.1 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 38 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 34 24.00 0 36 0 0
#> 165.2 24.00 0 47 0 0
#> 34.1 24.00 0 36 0 0
#> 72 24.00 0 40 0 1
#> 174.1 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.549 NA NA NA
#> 2 age, Cure model 0.00878 NA NA NA
#> 3 grade_ii, Cure model 0.0832 NA NA NA
#> 4 grade_iii, Cure model 0.854 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000896 NA NA NA
#> 2 grade_ii, Survival model 0.553 NA NA NA
#> 3 grade_iii, Survival model 0.167 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.548946 0.008776 0.083161 0.853719
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 248.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.548946427 0.008775645 0.083160741 0.853719460
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0008956884 0.5529223532 0.1669781861
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.81507840 0.96755870 0.13942410 0.04588845 0.56883262 0.70962905
#> [7] 0.89226977 0.34332925 0.21182840 0.99184512 0.54912688 0.50963863
#> [13] 0.64546724 0.48027937 0.84964274 0.40330324 0.58848135 0.17557091
#> [19] 0.23588438 0.40330324 0.87530500 0.28072260 0.79740533 0.61714821
#> [25] 0.75341920 0.48027937 0.28072260 0.66430548 0.73582954 0.45097127
#> [31] 0.90919630 0.04588845 0.66430548 0.51959173 0.84964274 0.87530500
#> [37] 0.11373630 0.57865255 0.70962905 0.00959298 0.38338761 0.61714821
#> [43] 0.76226936 0.53923501 0.95101054 0.80624041 0.94268430 0.08879261
#> [49] 0.81507840 0.07465714 0.58848135 0.16329581 0.55899130 0.18788627
#> [55] 0.93430785 0.32257169 0.40330324 0.86675931 0.78855791 0.48027937
#> [61] 0.32257169 0.66430548 0.73582954 0.40330324 0.36332941 0.12702723
#> [67] 0.84105222 0.45097127 0.25871083 0.45097127 0.70962905 0.25871083
#> [73] 0.30161882 0.34332925 0.08879261 0.24733231 0.13942410 0.63599296
#> [79] 0.95101054 0.64546724 0.69160853 0.96755870 0.76226936 0.90919630
#> [85] 0.51959173 0.89226977 0.36332941 0.30161882 0.92591853 0.96755870
#> [91] 0.02712071 0.18788627 0.38338761 0.76226936 0.40330324 0.69160853
#> [97] 0.83240439 0.22406093 0.60755555 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 60 70 15 164 45 18 43 158 136 77 117 108 100
#> 13.15 7.38 22.68 23.60 17.42 15.21 12.10 20.14 21.83 7.27 17.46 18.29 16.07
#> 8 177 58 106 66 153 55 42 32 13 85 180 8.1
#> 18.43 12.53 19.34 16.67 22.13 21.33 19.34 12.43 20.90 14.34 16.44 14.82 18.43
#> 32.1 167 157 179 107 164.1 167.1 51 177.1 42.1 113 23 18.1
#> 20.90 15.55 15.10 18.63 11.18 23.60 15.55 18.23 12.53 12.43 22.86 16.92 15.21
#> 78 170 192 133 110 16 81 187 69 60.1 129 106.1 194
#> 23.88 19.54 16.44 14.65 17.56 8.71 14.06 9.92 23.23 13.15 23.41 16.67 22.40
#> 111 175 101 128 58.1 37 96 8.2 128.1 167.2 157.1 55.1 105
#> 17.45 21.91 9.97 20.35 19.34 12.52 14.54 18.43 20.35 15.55 15.10 19.34 19.75
#> 63 140 179.1 90 179.2 18.2 90.1 68 158.1 69.1 36 15.1 188
#> 22.77 12.68 18.63 20.94 18.63 15.21 20.94 20.62 20.14 23.23 21.19 22.68 16.16
#> 16.1 100.1 29 70.1 133.1 107.1 51.1 43.1 105.1 68.1 159 70.2 168
#> 8.71 16.07 15.45 7.38 14.65 11.18 18.23 12.10 19.75 20.62 10.55 7.38 23.72
#> 175.1 170.1 133.2 55.2 29.1 123 197 181 109 67 98 148 94
#> 21.91 19.54 14.65 19.34 15.45 13.00 21.60 16.46 24.00 24.00 24.00 24.00 24.00
#> 118 151 47 75 22 98.1 21 19 64 119 137 94.1 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 191 151.1 120 135 186 46 182 109.1 121 151.2 62 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 64.1 196 148.1 11 20 82 46.1 2 172 102 146 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 31 161 186.1 62.1 162 137.1 193 198 44 74.1 141 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 147.1 160 174 65 132 198.1 46.2 28 196.1 165 65.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 198.2 126 121.1 64.2 143 148.2 176 131.1 1 38 34 165.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 72 174.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[22]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0007739037 0.6671660154 0.6652882444
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.083040526 -0.001858535 0.001223623
#> grade_iii, Cure model
#> 0.502546880
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 183 9.24 1 67 1 0
#> 50 10.02 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 59 10.16 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 25 6.32 1 34 1 0
#> 136 21.83 1 43 0 1
#> 56 12.21 1 60 0 0
#> 6 15.64 1 39 0 0
#> 52 10.42 1 52 0 1
#> 170 19.54 1 43 0 1
#> 190 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 184 17.77 1 38 0 0
#> 30 17.43 1 78 0 0
#> 171 16.57 1 41 0 1
#> 52.1 10.42 1 52 0 1
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 190.1 20.81 1 42 1 0
#> 26 15.77 1 49 0 1
#> 184.1 17.77 1 38 0 0
#> 8 18.43 1 32 0 0
#> 45 17.42 1 54 0 1
#> 49 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 42.1 12.43 1 49 0 1
#> 59.1 10.16 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 106 16.67 1 49 1 0
#> 166 19.98 1 48 0 0
#> 32 20.90 1 37 1 0
#> 192 16.44 1 31 1 0
#> 50.1 10.02 1 NA 1 0
#> 184.2 17.77 1 38 0 0
#> 170.1 19.54 1 43 0 1
#> 59.2 10.16 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 41 18.02 1 40 1 0
#> 5 16.43 1 51 0 1
#> 70 7.38 1 30 1 0
#> 130 16.47 1 53 0 1
#> 181 16.46 1 45 0 1
#> 50.2 10.02 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 192.1 16.44 1 31 1 0
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 36 21.19 1 48 0 1
#> 181.1 16.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 32.1 20.90 1 37 1 0
#> 16 8.71 1 71 0 1
#> 26.1 15.77 1 49 0 1
#> 110 17.56 1 65 0 1
#> 55 19.34 1 69 0 1
#> 155 13.08 1 26 0 0
#> 169 22.41 1 46 0 0
#> 23 16.92 1 61 0 0
#> 192.2 16.44 1 31 1 0
#> 15 22.68 1 48 0 0
#> 85 16.44 1 36 0 0
#> 15.1 22.68 1 48 0 0
#> 106.1 16.67 1 49 1 0
#> 24 23.89 1 38 0 0
#> 70.1 7.38 1 30 1 0
#> 145 10.07 1 65 1 0
#> 76.1 19.22 1 54 0 1
#> 88 18.37 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 81 14.06 1 34 0 0
#> 179.1 18.63 1 42 0 0
#> 77.1 7.27 1 67 0 1
#> 199.1 19.81 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 124 9.73 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 61 10.12 1 36 0 1
#> 88.1 18.37 1 47 0 0
#> 88.2 18.37 1 47 0 0
#> 59.3 10.16 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 30.1 17.43 1 78 0 0
#> 85.1 16.44 1 36 0 0
#> 85.2 16.44 1 36 0 0
#> 168 23.72 1 70 0 0
#> 167 15.55 1 56 1 0
#> 45.1 17.42 1 54 0 1
#> 105 19.75 1 60 0 0
#> 16.1 8.71 1 71 0 1
#> 59.4 10.16 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 40 18.00 1 28 1 0
#> 190.2 20.81 1 42 1 0
#> 78.1 23.88 1 43 0 0
#> 43 12.10 1 61 0 1
#> 108 18.29 1 39 0 1
#> 10 10.53 1 34 0 0
#> 61.1 10.12 1 36 0 1
#> 88.3 18.37 1 47 0 0
#> 187 9.92 1 39 1 0
#> 41.1 18.02 1 40 1 0
#> 129 23.41 1 53 1 0
#> 149 8.37 1 33 1 0
#> 25.1 6.32 1 34 1 0
#> 58 19.34 1 39 0 0
#> 61.2 10.12 1 36 0 1
#> 78.2 23.88 1 43 0 0
#> 149.1 8.37 1 33 1 0
#> 58.1 19.34 1 39 0 0
#> 156 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 82 24.00 0 34 0 0
#> 28 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 19.1 24.00 0 57 0 1
#> 200 24.00 0 64 0 0
#> 161 24.00 0 45 0 0
#> 12 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 191 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 119.1 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 147 24.00 0 76 1 0
#> 34 24.00 0 36 0 0
#> 47 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 33 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 27 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 142 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 74.1 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 1 24.00 0 23 1 0
#> 3 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 74.2 24.00 0 43 0 1
#> 80.1 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 200.1 24.00 0 64 0 0
#> 94 24.00 0 51 0 1
#> 185.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 109 24.00 0 48 0 0
#> 185.2 24.00 0 44 1 0
#> 200.2 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 185.3 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 38.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 185.4 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 161.1 24.00 0 45 0 0
#> 191.1 24.00 0 60 0 1
#> 198 24.00 0 66 0 1
#> 83 24.00 0 6 0 0
#> 109.1 24.00 0 48 0 0
#> 198.1 24.00 0 66 0 1
#> 186 24.00 0 45 1 0
#> 67.1 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 109.2 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 2 24.00 0 9 0 0
#> 147.1 24.00 0 76 1 0
#> 116 24.00 0 58 0 1
#> 172.1 24.00 0 41 0 0
#> 156.1 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 143.1 24.00 0 51 0 0
#> 174.2 24.00 0 49 1 0
#> 143.2 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 198.2 24.00 0 66 0 1
#> 196.1 24.00 0 19 0 0
#> 185.5 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0830 NA NA NA
#> 2 age, Cure model -0.00186 NA NA NA
#> 3 grade_ii, Cure model 0.00122 NA NA NA
#> 4 grade_iii, Cure model 0.503 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000774 NA NA NA
#> 2 grade_ii, Survival model 0.667 NA NA NA
#> 3 grade_iii, Survival model 0.665 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.083041 -0.001859 0.001224 0.502547
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 254.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.083040526 -0.001858535 0.001223623 0.502546880
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0007739037 0.6671660154 0.6652882444
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.93237070 0.60832982 0.80287019 0.98806066 0.23501719 0.85239525
#> [7] 0.78115866 0.88666703 0.38995661 0.32227742 0.97597519 0.57291623
#> [13] 0.62565606 0.68384482 0.88666703 0.35561001 0.79565727 0.32227742
#> [19] 0.76665484 0.57291623 0.48902010 0.64271141 0.85935150 0.83853417
#> [25] 0.83853417 0.28277191 0.66766293 0.36707335 0.29695646 0.71528787
#> [31] 0.57291623 0.38995661 0.16296572 0.54575205 0.75922421 0.96373074
#> [37] 0.69188774 0.69983582 0.87309316 0.71528787 0.46981256 0.26782140
#> [43] 0.69983582 0.25196999 0.45057916 0.29695646 0.93876483 0.76665484
#> [49] 0.59947988 0.41124545 0.81716649 0.21673234 0.65931388 0.71528787
#> [55] 0.18160433 0.71528787 0.18160433 0.66766293 0.02143494 0.96373074
#> [61] 0.91944396 0.45057916 0.49871525 0.82431253 0.81001918 0.46981256
#> [67] 0.97597519 0.61705479 0.05660188 0.89997951 0.49871525 0.49871525
#> [73] 0.83145487 0.62565606 0.71528787 0.71528787 0.11700254 0.78844246
#> [79] 0.64271141 0.37852318 0.93876483 0.41124545 0.56390861 0.32227742
#> [85] 0.05660188 0.86625064 0.53627592 0.87988079 0.89997951 0.49871525
#> [91] 0.92593008 0.54575205 0.14188039 0.95132961 0.98806066 0.41124545
#> [97] 0.89997951 0.05660188 0.95132961 0.41124545 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 183 117 96 25 136 56 6 52 170 190 77 184 30
#> 9.24 17.46 14.54 6.32 21.83 12.21 15.64 10.42 19.54 20.81 7.27 17.77 17.43
#> 171 52.1 150 180 190.1 26 184.1 8 45 49 42 42.1 90
#> 16.57 10.42 20.33 14.82 20.81 15.77 17.77 18.43 17.42 12.19 12.43 12.43 20.94
#> 106 166 32 192 184.2 170.1 92 41 5 70 130 181 107
#> 16.67 19.98 20.90 16.44 17.77 19.54 22.92 18.02 16.43 7.38 16.47 16.46 11.18
#> 192.1 179 36 181.1 153 76 32.1 16 26.1 110 55 155 169
#> 16.44 18.63 21.19 16.46 21.33 19.22 20.90 8.71 15.77 17.56 19.34 13.08 22.41
#> 23 192.2 15 85 15.1 106.1 24 70.1 145 76.1 88 177 81
#> 16.92 16.44 22.68 16.44 22.68 16.67 23.89 7.38 10.07 19.22 18.37 12.53 14.06
#> 179.1 77.1 111 78 61 88.1 88.2 37 30.1 85.1 85.2 168 167
#> 18.63 7.27 17.45 23.88 10.12 18.37 18.37 12.52 17.43 16.44 16.44 23.72 15.55
#> 45.1 105 16.1 55.1 40 190.2 78.1 43 108 10 61.1 88.3 187
#> 17.42 19.75 8.71 19.34 18.00 20.81 23.88 12.10 18.29 10.53 10.12 18.37 9.92
#> 41.1 129 149 25.1 58 61.2 78.2 149.1 58.1 156 95 178 80
#> 18.02 23.41 8.37 6.32 19.34 10.12 23.88 8.37 19.34 24.00 24.00 24.00 24.00
#> 137 172 19 82 28 119 19.1 200 161 12 174 191 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 21 71 174.1 147 34 47 74 54 33 38 98 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 142 65 74.1 1 3 144 84 84.1 74.2 80.1 185 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 185.1 64 109 185.2 200.2 196 131 143 185.3 65.1 31 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 38.1 162 31.1 185.4 131.1 161.1 191.1 198 83 109.1 198.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 163 109.2 103 2 147.1 116 172.1 156.1 11 143.1 174.2 143.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 198.2 196.1 185.5
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[23]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005726591 0.404364561 0.280690547
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.256079828 0.001729513 0.293202674
#> grade_iii, Cure model
#> 0.747386004
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 60 13.15 1 38 1 0
#> 101 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 70 7.38 1 30 1 0
#> 57 14.46 1 45 0 1
#> 158 20.14 1 74 1 0
#> 37 12.52 1 57 1 0
#> 169 22.41 1 46 0 0
#> 42.1 12.43 1 49 0 1
#> 32 20.90 1 37 1 0
#> 168 23.72 1 70 0 0
#> 169.1 22.41 1 46 0 0
#> 117 17.46 1 26 0 1
#> 192 16.44 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 158.1 20.14 1 74 1 0
#> 127 3.53 1 62 0 1
#> 170 19.54 1 43 0 1
#> 40 18.00 1 28 1 0
#> 60.2 13.15 1 38 1 0
#> 114 13.68 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 15 22.68 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 50.1 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 167 15.55 1 56 1 0
#> 42.2 12.43 1 49 0 1
#> 194 22.40 1 38 0 1
#> 129 23.41 1 53 1 0
#> 89 11.44 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 37.1 12.52 1 57 1 0
#> 23 16.92 1 61 0 0
#> 106.1 16.67 1 49 1 0
#> 6 15.64 1 39 0 0
#> 68 20.62 1 44 0 0
#> 101.1 9.97 1 10 0 1
#> 42.3 12.43 1 49 0 1
#> 85 16.44 1 36 0 0
#> 56 12.21 1 60 0 0
#> 77 7.27 1 67 0 1
#> 26 15.77 1 49 0 1
#> 92 22.92 1 47 0 1
#> 6.1 15.64 1 39 0 0
#> 113 22.86 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 166 19.98 1 48 0 0
#> 111 17.45 1 47 0 1
#> 39 15.59 1 37 0 1
#> 129.1 23.41 1 53 1 0
#> 4 17.64 1 NA 0 1
#> 190 20.81 1 42 1 0
#> 43 12.10 1 61 0 1
#> 187.1 9.92 1 39 1 0
#> 40.1 18.00 1 28 1 0
#> 96 14.54 1 33 0 1
#> 18 15.21 1 49 1 0
#> 166.1 19.98 1 48 0 0
#> 63 22.77 1 31 1 0
#> 133 14.65 1 57 0 0
#> 69 23.23 1 25 0 1
#> 14 12.89 1 21 0 0
#> 36 21.19 1 48 0 1
#> 170.1 19.54 1 43 0 1
#> 69.1 23.23 1 25 0 1
#> 190.1 20.81 1 42 1 0
#> 127.1 3.53 1 62 0 1
#> 6.2 15.64 1 39 0 0
#> 6.3 15.64 1 39 0 0
#> 110.1 17.56 1 65 0 1
#> 114.1 13.68 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 154 12.63 1 20 1 0
#> 123 13.00 1 44 1 0
#> 184.1 17.77 1 38 0 0
#> 52 10.42 1 52 0 1
#> 164 23.60 1 76 0 1
#> 110.2 17.56 1 65 0 1
#> 37.2 12.52 1 57 1 0
#> 23.1 16.92 1 61 0 0
#> 133.1 14.65 1 57 0 0
#> 183 9.24 1 67 1 0
#> 45 17.42 1 54 0 1
#> 110.3 17.56 1 65 0 1
#> 37.3 12.52 1 57 1 0
#> 23.2 16.92 1 61 0 0
#> 60.3 13.15 1 38 1 0
#> 170.2 19.54 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 16 8.71 1 71 0 1
#> 195 11.76 1 NA 1 0
#> 50.2 10.02 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 97 19.14 1 65 0 1
#> 192.2 16.44 1 31 1 0
#> 29 15.45 1 68 1 0
#> 60.4 13.15 1 38 1 0
#> 150 20.33 1 48 0 0
#> 88 18.37 1 47 0 0
#> 61 10.12 1 36 0 1
#> 51.1 18.23 1 83 0 1
#> 60.5 13.15 1 38 1 0
#> 171 16.57 1 41 0 1
#> 123.1 13.00 1 44 1 0
#> 183.1 9.24 1 67 1 0
#> 181 16.46 1 45 0 1
#> 65 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 67 24.00 0 25 0 0
#> 48 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 46 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 82 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 46.1 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 109.1 24.00 0 48 0 0
#> 176.1 24.00 0 43 0 1
#> 174 24.00 0 49 1 0
#> 28 24.00 0 67 1 0
#> 1 24.00 0 23 1 0
#> 20 24.00 0 46 1 0
#> 84 24.00 0 39 0 1
#> 118 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 118.1 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 12 24.00 0 63 0 0
#> 200 24.00 0 64 0 0
#> 46.2 24.00 0 71 0 0
#> 156.1 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 74 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 19.1 24.00 0 57 0 1
#> 172 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 176.2 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 144 24.00 0 28 0 1
#> 115 24.00 0 NA 1 0
#> 186 24.00 0 45 1 0
#> 144.1 24.00 0 28 0 1
#> 161 24.00 0 45 0 0
#> 87 24.00 0 27 0 0
#> 142 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 146 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 103.1 24.00 0 56 1 0
#> 121.1 24.00 0 57 1 0
#> 172.1 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 156.2 24.00 0 50 1 0
#> 21 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 112.1 24.00 0 61 0 0
#> 2 24.00 0 9 0 0
#> 73.1 24.00 0 NA 0 1
#> 17 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 74.1 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 1.1 24.00 0 23 1 0
#> 33 24.00 0 53 0 0
#> 144.2 24.00 0 28 0 1
#> 116 24.00 0 58 0 1
#> 71.1 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 22.1 24.00 0 52 1 0
#> 148 24.00 0 61 1 0
#> 33.1 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 47.1 24.00 0 38 0 1
#> 161.1 24.00 0 45 0 0
#> 1.2 24.00 0 23 1 0
#> 98 24.00 0 34 1 0
#> 72 24.00 0 40 0 1
#> 67.1 24.00 0 25 0 0
#> 7.1 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.256 NA NA NA
#> 2 age, Cure model 0.00173 NA NA NA
#> 3 grade_ii, Cure model 0.293 NA NA NA
#> 4 grade_iii, Cure model 0.747 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00573 NA NA NA
#> 2 grade_ii, Survival model 0.404 NA NA NA
#> 3 grade_iii, Survival model 0.281 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.25608 0.00173 0.29320 0.74739
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 252.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.256079828 0.001729513 0.293202674 0.747386004
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005726591 0.404364561 0.280690547
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.911670404 0.666137939 0.891988343 0.813189363 0.960715847 0.655883819
#> [7] 0.187311065 0.774209951 0.100314128 0.813189363 0.139445175 0.003046188
#> [13] 0.100314128 0.383818429 0.495156698 0.666137939 0.187311065 0.980388395
#> [19] 0.226026849 0.304833785 0.666137939 0.284714184 0.090660248 0.324593545
#> [25] 0.454351815 0.594646356 0.813189363 0.119515493 0.026103483 0.344591686
#> [31] 0.774209951 0.424062020 0.454351815 0.544542808 0.167826106 0.891988343
#> [37] 0.813189363 0.495156698 0.852168970 0.970547243 0.534439261 0.062083153
#> [43] 0.544542808 0.071551251 0.264571225 0.206450363 0.403812755 0.584423214
#> [49] 0.026103483 0.149259497 0.862119304 0.911670404 0.304833785 0.645625972
#> [55] 0.615059424 0.206450363 0.081247948 0.625242407 0.044567312 0.754214308
#> [61] 0.129482379 0.226026849 0.044567312 0.149259497 0.980388395 0.544542808
#> [67] 0.544542808 0.344591686 0.495156698 0.764234114 0.734337532 0.324593545
#> [73] 0.872077263 0.013558333 0.344591686 0.774209951 0.424062020 0.625242407
#> [79] 0.931268521 0.413933897 0.344591686 0.774209951 0.424062020 0.666137939
#> [85] 0.226026849 0.724285888 0.950858039 0.383818429 0.254623979 0.495156698
#> [91] 0.604854185 0.666137939 0.177504281 0.274599107 0.882037150 0.284714184
#> [97] 0.666137939 0.474656219 0.734337532 0.931268521 0.484908974 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 187 60 101 42 70 57 158 37 169 42.1 32 168 169.1
#> 9.92 13.15 9.97 12.43 7.38 14.46 20.14 12.52 22.41 12.43 20.90 23.72 22.41
#> 117 192 60.1 158.1 127 170 40 60.2 51 15 184 106 167
#> 17.46 16.44 13.15 20.14 3.53 19.54 18.00 13.15 18.23 22.68 17.77 16.67 15.55
#> 42.2 194 129 110 37.1 23 106.1 6 68 101.1 42.3 85 56
#> 12.43 22.40 23.41 17.56 12.52 16.92 16.67 15.64 20.62 9.97 12.43 16.44 12.21
#> 77 26 92 6.1 113 179 166 111 39 129.1 190 43 187.1
#> 7.27 15.77 22.92 15.64 22.86 18.63 19.98 17.45 15.59 23.41 20.81 12.10 9.92
#> 40.1 96 18 166.1 63 133 69 14 36 170.1 69.1 190.1 127.1
#> 18.00 14.54 15.21 19.98 22.77 14.65 23.23 12.89 21.19 19.54 23.23 20.81 3.53
#> 6.2 6.3 110.1 192.1 154 123 184.1 52 164 110.2 37.2 23.1 133.1
#> 15.64 15.64 17.56 16.44 12.63 13.00 17.77 10.42 23.60 17.56 12.52 16.92 14.65
#> 183 45 110.3 37.3 23.2 60.3 170.2 155 16 117.1 97 192.2 29
#> 9.24 17.42 17.56 12.52 16.92 13.15 19.54 13.08 8.71 17.46 19.14 16.44 15.45
#> 60.4 150 88 61 51.1 60.5 171 123.1 183.1 181 65 34 67
#> 13.15 20.33 18.37 10.12 18.23 13.15 16.57 13.00 9.24 16.46 24.00 24.00 24.00
#> 48 7 46 82 109 198 176 147 46.1 156 109.1 176.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 1 20 84 118 11 118.1 47 103 12 200 46.2 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 19 102 178 160 147.1 74 196 19.1 172 121 176.2 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 53 144 186 144.1 161 87 142 94 146 64 103.1 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 71 185 156.2 21 112 112.1 2 17 186.1 74.1 152 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 33 144.2 116 71.1 151 22.1 148 33.1 34.1 47.1 161.1 1.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 72 67.1 7.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[24]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.03768737 1.25805603 0.58237856
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.568402264 -0.006271125 -0.636295978
#> grade_iii, Cure model
#> 0.455008270
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 171 16.57 1 41 0 1
#> 60 13.15 1 38 1 0
#> 136 21.83 1 43 0 1
#> 42 12.43 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 175 21.91 1 43 0 0
#> 175.1 21.91 1 43 0 0
#> 42.1 12.43 1 49 0 1
#> 175.2 21.91 1 43 0 0
#> 90 20.94 1 50 0 1
#> 187 9.92 1 39 1 0
#> 23 16.92 1 61 0 0
#> 187.1 9.92 1 39 1 0
#> 50 10.02 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 158 20.14 1 74 1 0
#> 197 21.60 1 69 1 0
#> 145 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 166 19.98 1 48 0 0
#> 101 9.97 1 10 0 1
#> 124 9.73 1 NA 1 0
#> 171.1 16.57 1 41 0 1
#> 149 8.37 1 33 1 0
#> 36 21.19 1 48 0 1
#> 114.1 13.68 1 NA 0 0
#> 154 12.63 1 20 1 0
#> 25 6.32 1 34 1 0
#> 168 23.72 1 70 0 0
#> 36.1 21.19 1 48 0 1
#> 40 18.00 1 28 1 0
#> 85 16.44 1 36 0 0
#> 52 10.42 1 52 0 1
#> 113.1 22.86 1 34 0 0
#> 133 14.65 1 57 0 0
#> 129 23.41 1 53 1 0
#> 108 18.29 1 39 0 1
#> 23.1 16.92 1 61 0 0
#> 81 14.06 1 34 0 0
#> 15 22.68 1 48 0 0
#> 168.1 23.72 1 70 0 0
#> 92 22.92 1 47 0 1
#> 77 7.27 1 67 0 1
#> 108.1 18.29 1 39 0 1
#> 189 10.51 1 NA 1 0
#> 149.1 8.37 1 33 1 0
#> 166.1 19.98 1 48 0 0
#> 184 17.77 1 38 0 0
#> 184.1 17.77 1 38 0 0
#> 23.2 16.92 1 61 0 0
#> 134 17.81 1 47 1 0
#> 6 15.64 1 39 0 0
#> 158.1 20.14 1 74 1 0
#> 155 13.08 1 26 0 0
#> 166.2 19.98 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 15.1 22.68 1 48 0 0
#> 93 10.33 1 52 0 1
#> 159 10.55 1 50 0 1
#> 133.1 14.65 1 57 0 0
#> 114.2 13.68 1 NA 0 0
#> 155.1 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 60.1 13.15 1 38 1 0
#> 167 15.55 1 56 1 0
#> 169 22.41 1 46 0 0
#> 88 18.37 1 47 0 0
#> 164.1 23.60 1 76 0 1
#> 105 19.75 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 187.2 9.92 1 39 1 0
#> 114.3 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 100 16.07 1 60 0 0
#> 101.1 9.97 1 10 0 1
#> 187.3 9.92 1 39 1 0
#> 105.1 19.75 1 60 0 0
#> 58 19.34 1 39 0 0
#> 97 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 197.1 21.60 1 69 1 0
#> 4 17.64 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 4.1 17.64 1 NA 0 1
#> 49 12.19 1 48 1 0
#> 50.1 10.02 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 96 14.54 1 33 0 1
#> 51 18.23 1 83 0 1
#> 101.2 9.97 1 10 0 1
#> 66.1 22.13 1 53 0 0
#> 79 16.23 1 54 1 0
#> 15.2 22.68 1 48 0 0
#> 124.2 9.73 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 88.1 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 199 19.81 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 66.2 22.13 1 53 0 0
#> 117.1 17.46 1 26 0 1
#> 183.1 9.24 1 67 1 0
#> 187.4 9.92 1 39 1 0
#> 181 16.46 1 45 0 1
#> 18 15.21 1 49 1 0
#> 39.1 15.59 1 37 0 1
#> 121 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 72 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 54.1 24.00 0 53 1 0
#> 67 24.00 0 25 0 0
#> 185 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 120 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 95 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 73 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 38 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 9 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 109 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 9.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 103 24.00 0 56 1 0
#> 54.2 24.00 0 53 1 0
#> 191 24.00 0 60 0 1
#> 196 24.00 0 19 0 0
#> 19.1 24.00 0 57 0 1
#> 84 24.00 0 39 0 1
#> 82 24.00 0 34 0 0
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 142 24.00 0 53 0 0
#> 53.1 24.00 0 32 0 1
#> 178.1 24.00 0 52 1 0
#> 3 24.00 0 31 1 0
#> 67.1 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 21.2 24.00 0 47 0 0
#> 141.2 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 138.1 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 87 24.00 0 27 0 0
#> 103.1 24.00 0 56 1 0
#> 35.1 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 115.1 24.00 0 NA 1 0
#> 48 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 147.1 24.00 0 76 1 0
#> 75 24.00 0 21 1 0
#> 198 24.00 0 66 0 1
#> 131.1 24.00 0 66 0 0
#> 122.2 24.00 0 66 0 0
#> 198.1 24.00 0 66 0 1
#> 98 24.00 0 34 1 0
#> 47 24.00 0 38 0 1
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 34.1 24.00 0 36 0 0
#> 65.1 24.00 0 57 1 0
#> 98.1 24.00 0 34 1 0
#> 198.2 24.00 0 66 0 1
#> 27 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 98.2 24.00 0 34 1 0
#> 115.2 24.00 0 NA 1 0
#> 74 24.00 0 43 0 1
#> 62.1 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 1 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 33 24.00 0 53 0 0
#> 121.2 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.568 NA NA NA
#> 2 age, Cure model -0.00627 NA NA NA
#> 3 grade_ii, Cure model -0.636 NA NA NA
#> 4 grade_iii, Cure model 0.455 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0377 NA NA NA
#> 2 grade_ii, Survival model 1.26 NA NA NA
#> 3 grade_iii, Survival model 0.582 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.568402 -0.006271 -0.636296 0.455008
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.2
#> Residual Deviance: 242.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.568402264 -0.006271125 -0.636295978 0.455008270
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.03768737 1.25805603 0.58237856
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.412611e-01 1.452317e-01 3.906221e-01 1.165164e-03 4.885244e-01
#> [6] 2.076348e-02 4.762236e-04 4.762236e-04 4.885244e-01 4.762236e-04
#> [11] 4.338847e-03 7.117445e-01 1.176280e-01 7.117445e-01 3.115336e-09
#> [16] 5.201321e-03 1.525949e-03 6.197638e-01 9.739273e-01 8.065864e-06
#> [21] 7.280080e-03 6.438422e-01 1.452317e-01 8.737933e-01 2.448520e-03
#> [26] 4.685994e-01 9.484193e-01 2.624835e-15 2.448520e-03 6.768774e-02
#> [31] 1.771451e-01 5.735449e-01 8.065864e-06 3.180288e-01 9.893466e-07
#> [36] 4.425733e-02 1.176280e-01 3.715038e-01 2.644244e-05 2.624835e-15
#> [41] 3.326799e-06 9.229272e-01 4.425733e-02 8.737933e-01 7.280080e-03
#> [46] 8.046332e-02 8.046332e-02 1.176280e-01 7.396473e-02 2.138836e-01
#> [51] 5.201321e-03 4.285032e-01 7.280080e-03 2.138836e-01 2.644244e-05
#> [56] 5.963196e-01 5.514271e-01 3.180288e-01 4.285032e-01 2.448520e-03
#> [61] 3.906221e-01 2.704842e-01 1.049731e-04 3.485084e-02 3.115336e-09
#> [66] 1.159990e-02 7.117445e-01 1.605772e-04 6.127764e-02 2.010377e-01
#> [71] 6.438422e-01 7.117445e-01 1.159990e-02 1.567127e-02 2.703647e-02
#> [76] 3.077010e-02 1.525949e-03 8.246202e-01 2.076348e-02 1.094799e-01
#> [81] 5.299367e-01 1.567127e-02 3.530708e-01 5.501268e-02 6.438422e-01
#> [86] 1.605772e-04 1.888873e-01 2.644244e-05 2.704842e-01 3.485084e-02
#> [91] 9.460547e-02 1.605772e-04 9.460547e-02 8.246202e-01 7.117445e-01
#> [96] 1.659537e-01 3.016396e-01 2.412611e-01 0.000000e+00 0.000000e+00
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 39 171 60 136 42 76 175 175.1 42.1 175.2 90 187 23
#> 15.59 16.57 13.15 21.83 12.43 19.22 21.91 21.91 12.43 21.91 20.94 9.92 16.92
#> 187.1 164 158 197 145 127 113 166 101 171.1 149 36 154
#> 9.92 23.60 20.14 21.60 10.07 3.53 22.86 19.98 9.97 16.57 8.37 21.19 12.63
#> 25 168 36.1 40 85 52 113.1 133 129 108 23.1 81 15
#> 6.32 23.72 21.19 18.00 16.44 10.42 22.86 14.65 23.41 18.29 16.92 14.06 22.68
#> 168.1 92 77 108.1 149.1 166.1 184 184.1 23.2 134 6 158.1 155
#> 23.72 22.92 7.27 18.29 8.37 19.98 17.77 17.77 16.92 17.81 15.64 20.14 13.08
#> 166.2 6.1 15.1 93 159 133.1 155.1 99 60.1 167 169 88 164.1
#> 19.98 15.64 22.68 10.33 10.55 14.65 13.08 21.19 13.15 15.55 22.41 18.37 23.60
#> 105 187.2 66 41 100 101.1 187.3 105.1 58 97 8 197.1 183
#> 19.75 9.92 22.13 18.02 16.07 9.97 9.92 19.75 19.34 19.14 18.43 21.60 9.24
#> 76.1 45 49 58.1 96 51 101.2 66.1 79 15.2 167.1 88.1 117
#> 19.22 17.42 12.19 19.34 14.54 18.23 9.97 22.13 16.23 22.68 15.55 18.37 17.46
#> 66.2 117.1 183.1 187.4 181 18 39.1 121 54 72 19 54.1 67
#> 22.13 17.46 9.24 9.92 16.46 15.21 15.59 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 178 28 120 147 95 141 118 2 38 34 9 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 109 131 9.1 46 135 103 54.2 191 196 19.1 84 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 21.1 138 53 142 53.1 178.1 3 67.1 200 21.2 141.2 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 161 138.1 62 193 87 103.1 35.1 200.1 48 3.1 122.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.1 75 198 131.1 122.2 198.1 98 47 71 17 137 148.1 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 98.1 198.2 27 121.1 98.2 74 62.1 174 1 119 33 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[25]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01176925 0.83156195 0.45127165
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91893493 0.02406253 -0.60722984
#> grade_iii, Cure model
#> 0.82626789
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 164 23.60 1 76 0 1
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 25 6.32 1 34 1 0
#> 194 22.40 1 38 0 1
#> 177 12.53 1 75 0 0
#> 169 22.41 1 46 0 0
#> 10 10.53 1 34 0 0
#> 175 21.91 1 43 0 0
#> 183 9.24 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 25.1 6.32 1 34 1 0
#> 26 15.77 1 49 0 1
#> 39 15.59 1 37 0 1
#> 97 19.14 1 65 0 1
#> 26.1 15.77 1 49 0 1
#> 127 3.53 1 62 0 1
#> 136 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 42 12.43 1 49 0 1
#> 16 8.71 1 71 0 1
#> 189.1 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 187 9.92 1 39 1 0
#> 56 12.21 1 60 0 0
#> 168 23.72 1 70 0 0
#> 117 17.46 1 26 0 1
#> 177.1 12.53 1 75 0 0
#> 175.2 21.91 1 43 0 0
#> 125 15.65 1 67 1 0
#> 78 23.88 1 43 0 0
#> 166 19.98 1 48 0 0
#> 5 16.43 1 51 0 1
#> 159 10.55 1 50 0 1
#> 133 14.65 1 57 0 0
#> 150.1 20.33 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 180 14.82 1 37 0 0
#> 194.1 22.40 1 38 0 1
#> 8 18.43 1 32 0 0
#> 14 12.89 1 21 0 0
#> 195 11.76 1 NA 1 0
#> 78.1 23.88 1 43 0 0
#> 140 12.68 1 59 1 0
#> 187.1 9.92 1 39 1 0
#> 125.1 15.65 1 67 1 0
#> 168.1 23.72 1 70 0 0
#> 41 18.02 1 40 1 0
#> 56.1 12.21 1 60 0 0
#> 129 23.41 1 53 1 0
#> 133.1 14.65 1 57 0 0
#> 96 14.54 1 33 0 1
#> 13 14.34 1 54 0 1
#> 106 16.67 1 49 1 0
#> 168.2 23.72 1 70 0 0
#> 56.2 12.21 1 60 0 0
#> 43 12.10 1 61 0 1
#> 171 16.57 1 41 0 1
#> 107 11.18 1 54 1 0
#> 43.1 12.10 1 61 0 1
#> 68 20.62 1 44 0 0
#> 149 8.37 1 33 1 0
#> 123 13.00 1 44 1 0
#> 100 16.07 1 60 0 0
#> 150.2 20.33 1 48 0 0
#> 164.1 23.60 1 76 0 1
#> 145 10.07 1 65 1 0
#> 37 12.52 1 57 1 0
#> 61 10.12 1 36 0 1
#> 184 17.77 1 38 0 0
#> 136.1 21.83 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 184.1 17.77 1 38 0 0
#> 190 20.81 1 42 1 0
#> 153 21.33 1 55 1 0
#> 164.2 23.60 1 76 0 1
#> 113 22.86 1 34 0 0
#> 29 15.45 1 68 1 0
#> 55 19.34 1 69 0 1
#> 177.2 12.53 1 75 0 0
#> 134 17.81 1 47 1 0
#> 111 17.45 1 47 0 1
#> 129.1 23.41 1 53 1 0
#> 76.1 19.22 1 54 0 1
#> 18.1 15.21 1 49 1 0
#> 15 22.68 1 48 0 0
#> 168.3 23.72 1 70 0 0
#> 39.1 15.59 1 37 0 1
#> 188 16.16 1 46 0 1
#> 16.1 8.71 1 71 0 1
#> 32 20.90 1 37 1 0
#> 101 9.97 1 10 0 1
#> 86 23.81 1 58 0 1
#> 166.1 19.98 1 48 0 0
#> 5.1 16.43 1 51 0 1
#> 92 22.92 1 47 0 1
#> 91 5.33 1 61 0 1
#> 77 7.27 1 67 0 1
#> 168.4 23.72 1 70 0 0
#> 40 18.00 1 28 1 0
#> 14.1 12.89 1 21 0 0
#> 85 16.44 1 36 0 0
#> 36 21.19 1 48 0 1
#> 184.2 17.77 1 38 0 0
#> 134.1 17.81 1 47 1 0
#> 177.3 12.53 1 75 0 0
#> 125.2 15.65 1 67 1 0
#> 101.1 9.97 1 10 0 1
#> 194.2 22.40 1 38 0 1
#> 33 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 147 24.00 0 76 1 0
#> 1 24.00 0 23 1 0
#> 162 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 65 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 54 24.00 0 53 1 0
#> 165 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 48 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 17 24.00 0 38 0 1
#> 54.1 24.00 0 53 1 0
#> 74 24.00 0 43 0 1
#> 161 24.00 0 45 0 0
#> 94 24.00 0 51 0 1
#> 120 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 87 24.00 0 27 0 0
#> 161.1 24.00 0 45 0 0
#> 27 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 161.2 24.00 0 45 0 0
#> 73 24.00 0 NA 0 1
#> 176 24.00 0 43 0 1
#> 87.1 24.00 0 27 0 0
#> 141 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 98 24.00 0 34 1 0
#> 178 24.00 0 52 1 0
#> 27.1 24.00 0 63 1 0
#> 103 24.00 0 56 1 0
#> 193 24.00 0 45 0 1
#> 160 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 102.1 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 173 24.00 0 19 0 1
#> 54.2 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 118 24.00 0 44 1 0
#> 27.2 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 152 24.00 0 36 0 1
#> 185.1 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 1.2 24.00 0 23 1 0
#> 98.1 24.00 0 34 1 0
#> 200 24.00 0 64 0 0
#> 174 24.00 0 49 1 0
#> 35 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 75 24.00 0 21 1 0
#> 3 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 196 24.00 0 19 0 0
#> 98.2 24.00 0 34 1 0
#> 161.3 24.00 0 45 0 0
#> 137 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 178.1 24.00 0 52 1 0
#> 151 24.00 0 42 0 0
#> 135.2 24.00 0 58 1 0
#> 135.3 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 173.2 24.00 0 19 0 1
#> 102.2 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 104 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 122.1 24.00 0 66 0 0
#> 33.1 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 103.2 24.00 0 56 1 0
#> 35.1 24.00 0 51 0 0
#> 98.3 24.00 0 34 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.919 NA NA NA
#> 2 age, Cure model 0.0241 NA NA NA
#> 3 grade_ii, Cure model -0.607 NA NA NA
#> 4 grade_iii, Cure model 0.826 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0118 NA NA NA
#> 2 grade_ii, Survival model 0.832 NA NA NA
#> 3 grade_iii, Survival model 0.451 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91893 0.02406 -0.60723 0.82627
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 247 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91893493 0.02406253 -0.60722984 0.82626789
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01176925 0.83156195 0.45127165
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.033755377 0.764532726 0.260567617 0.957781090 0.102325225 0.669676470
#> [7] 0.093662270 0.818621214 0.126179227 0.893935636 0.957781090 0.477718835
#> [13] 0.527756362 0.299719050 0.477718835 0.989382686 0.151979863 0.280027958
#> [19] 0.721831814 0.915105434 0.214571840 0.126179227 0.872743801 0.732447764
#> [25] 0.010243485 0.388183092 0.669676470 0.126179227 0.497888613 0.001182539
#> [31] 0.241583365 0.437736250 0.807764363 0.587946496 0.214571840 0.893935636
#> [37] 0.577859465 0.102325225 0.309822763 0.639016040 0.001182539 0.659418566
#> [43] 0.872743801 0.497888613 0.010243485 0.320030967 0.732447764 0.055115406
#> [49] 0.587946496 0.608285688 0.618530538 0.408036173 0.010243485 0.732447764
#> [55] 0.775334085 0.417904943 0.796926187 0.775334085 0.205668381 0.936432685
#> [61] 0.628804028 0.467576274 0.214571840 0.033755377 0.840426302 0.711234238
#> [67] 0.829525761 0.359079481 0.151979863 0.557982897 0.359079481 0.196918069
#> [73] 0.169821027 0.033755377 0.077319891 0.547848791 0.260567617 0.669676470
#> [79] 0.339972066 0.398097639 0.055115406 0.280027958 0.557982897 0.085322111
#> [85] 0.010243485 0.527756362 0.457543932 0.915105434 0.188009063 0.851317124
#> [91] 0.006211709 0.241583365 0.437736250 0.069582228 0.978792989 0.947089667
#> [97] 0.010243485 0.330099674 0.639016040 0.427780904 0.178890167 0.359079481
#> [103] 0.339972066 0.669676470 0.497888613 0.851317124 0.102325225 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 164 49 58 25 194 177 169 10 175 183 25.1 26 39
#> 23.60 12.19 19.34 6.32 22.40 12.53 22.41 10.53 21.91 9.24 6.32 15.77 15.59
#> 97 26.1 127 136 76 42 16 150 175.1 187 56 168 117
#> 19.14 15.77 3.53 21.83 19.22 12.43 8.71 20.33 21.91 9.92 12.21 23.72 17.46
#> 177.1 175.2 125 78 166 5 159 133 150.1 183.1 180 194.1 8
#> 12.53 21.91 15.65 23.88 19.98 16.43 10.55 14.65 20.33 9.24 14.82 22.40 18.43
#> 14 78.1 140 187.1 125.1 168.1 41 56.1 129 133.1 96 13 106
#> 12.89 23.88 12.68 9.92 15.65 23.72 18.02 12.21 23.41 14.65 14.54 14.34 16.67
#> 168.2 56.2 43 171 107 43.1 68 149 123 100 150.2 164.1 145
#> 23.72 12.21 12.10 16.57 11.18 12.10 20.62 8.37 13.00 16.07 20.33 23.60 10.07
#> 37 61 184 136.1 18 184.1 190 153 164.2 113 29 55 177.2
#> 12.52 10.12 17.77 21.83 15.21 17.77 20.81 21.33 23.60 22.86 15.45 19.34 12.53
#> 134 111 129.1 76.1 18.1 15 168.3 39.1 188 16.1 32 101 86
#> 17.81 17.45 23.41 19.22 15.21 22.68 23.72 15.59 16.16 8.71 20.90 9.97 23.81
#> 166.1 5.1 92 91 77 168.4 40 14.1 85 36 184.2 134.1 177.3
#> 19.98 16.43 22.92 5.33 7.27 23.72 18.00 12.89 16.44 21.19 17.77 17.81 12.53
#> 125.2 101.1 194.2 33 7 147 1 162 121 185 182 65 67
#> 15.65 9.97 22.40 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 165 198 48 1.1 17 54.1 74 161 94 120 102 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 27 121.1 142 161.2 176 87.1 141 135 98 178 27.1 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 160 135.1 102.1 146 173 54.2 122 173.1 118 27.2 112 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 185.1 103.1 1.2 98.1 200 174 35 34 75 3 28 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 161.3 137 44 178.1 151 135.2 135.3 138 109 53 80 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.2 46 104 47 2 122.1 33.1 95 103.2 35.1 98.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[26]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002454351 1.144113831 0.396427805
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.49364419 0.01313825 -0.51714162
#> grade_iii, Cure model
#> 0.74440513
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 10.1 10.53 1 34 0 0
#> 43 12.10 1 61 0 1
#> 140 12.68 1 59 1 0
#> 114 13.68 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 105 19.75 1 60 0 0
#> 110 17.56 1 65 0 1
#> 179 18.63 1 42 0 0
#> 189 10.51 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 86 23.81 1 58 0 1
#> 36 21.19 1 48 0 1
#> 136 21.83 1 43 0 1
#> 149 8.37 1 33 1 0
#> 127 3.53 1 62 0 1
#> 43.1 12.10 1 61 0 1
#> 188 16.16 1 46 0 1
#> 187 9.92 1 39 1 0
#> 154 12.63 1 20 1 0
#> 124.1 9.73 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 57 14.46 1 45 0 1
#> 189.1 10.51 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 130 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 41 18.02 1 40 1 0
#> 149.1 8.37 1 33 1 0
#> 18 15.21 1 49 1 0
#> 128 20.35 1 35 0 1
#> 60 13.15 1 38 1 0
#> 199 19.81 1 NA 0 1
#> 130.1 16.47 1 53 0 1
#> 60.1 13.15 1 38 1 0
#> 59 10.16 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 60.2 13.15 1 38 1 0
#> 189.2 10.51 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 107 11.18 1 54 1 0
#> 56 12.21 1 60 0 0
#> 150 20.33 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 130.2 16.47 1 53 0 1
#> 58.1 19.34 1 39 0 0
#> 4.1 17.64 1 NA 0 1
#> 91 5.33 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 81 14.06 1 34 0 0
#> 188.1 16.16 1 46 0 1
#> 184 17.77 1 38 0 0
#> 164 23.60 1 76 0 1
#> 140.1 12.68 1 59 1 0
#> 37 12.52 1 57 1 0
#> 86.1 23.81 1 58 0 1
#> 23.1 16.92 1 61 0 0
#> 40 18.00 1 28 1 0
#> 43.2 12.10 1 61 0 1
#> 125 15.65 1 67 1 0
#> 123 13.00 1 44 1 0
#> 13 14.34 1 54 0 1
#> 15 22.68 1 48 0 0
#> 15.1 22.68 1 48 0 0
#> 171 16.57 1 41 0 1
#> 169 22.41 1 46 0 0
#> 30.1 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 8 18.43 1 32 0 0
#> 150.1 20.33 1 48 0 0
#> 166 19.98 1 48 0 0
#> 91.2 5.33 1 61 0 1
#> 43.3 12.10 1 61 0 1
#> 169.1 22.41 1 46 0 0
#> 195 11.76 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 79 16.23 1 54 1 0
#> 134 17.81 1 47 1 0
#> 77 7.27 1 67 0 1
#> 181 16.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 105.1 19.75 1 60 0 0
#> 187.1 9.92 1 39 1 0
#> 134.1 17.81 1 47 1 0
#> 52 10.42 1 52 0 1
#> 154.1 12.63 1 20 1 0
#> 184.1 17.77 1 38 0 0
#> 29 15.45 1 68 1 0
#> 55 19.34 1 69 0 1
#> 14 12.89 1 21 0 0
#> 111.1 17.45 1 47 0 1
#> 85 16.44 1 36 0 0
#> 105.2 19.75 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 99 21.19 1 38 0 1
#> 24 23.89 1 38 0 0
#> 52.1 10.42 1 52 0 1
#> 195.1 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 105.3 19.75 1 60 0 0
#> 194.1 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 15.2 22.68 1 48 0 0
#> 68.2 20.62 1 44 0 0
#> 15.3 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 89 11.44 1 NA 0 0
#> 55.1 19.34 1 69 0 1
#> 41.1 18.02 1 40 1 0
#> 100 16.07 1 60 0 0
#> 22 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 64 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 17 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 28 24.00 0 67 1 0
#> 20 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 174 24.00 0 49 1 0
#> 112 24.00 0 61 0 0
#> 87 24.00 0 27 0 0
#> 126 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 178 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 84 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 27 24.00 0 63 1 0
#> 126.1 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 135.1 24.00 0 58 1 0
#> 137 24.00 0 45 1 0
#> 54.1 24.00 0 53 1 0
#> 72 24.00 0 40 0 1
#> 196 24.00 0 19 0 0
#> 1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 67.1 24.00 0 25 0 0
#> 48 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 75 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 1.2 24.00 0 23 1 0
#> 35 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 73.1 24.00 0 NA 0 1
#> 31 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 162 24.00 0 51 0 0
#> 67.2 24.00 0 25 0 0
#> 103 24.00 0 56 1 0
#> 94.1 24.00 0 51 0 1
#> 7 24.00 0 37 1 0
#> 98 24.00 0 34 1 0
#> 162.1 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 135.2 24.00 0 58 1 0
#> 146 24.00 0 63 1 0
#> 95.1 24.00 0 68 0 1
#> 20.1 24.00 0 46 1 0
#> 80.1 24.00 0 41 0 0
#> 75.1 24.00 0 21 1 0
#> 1.3 24.00 0 23 1 0
#> 116.1 24.00 0 58 0 1
#> 44.1 24.00 0 56 0 0
#> 135.3 24.00 0 58 1 0
#> 141 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 142.1 24.00 0 53 0 0
#> 54.2 24.00 0 53 1 0
#> 67.3 24.00 0 25 0 0
#> 103.1 24.00 0 56 1 0
#> 2 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 138.1 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 115 24.00 0 NA 1 0
#> 22.1 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 135.4 24.00 0 58 1 0
#> 48.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.494 NA NA NA
#> 2 age, Cure model 0.0131 NA NA NA
#> 3 grade_ii, Cure model -0.517 NA NA NA
#> 4 grade_iii, Cure model 0.744 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00245 NA NA NA
#> 2 grade_ii, Survival model 1.14 NA NA NA
#> 3 grade_iii, Survival model 0.396 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49364 0.01314 -0.51714 0.74441
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 240.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49364419 0.01313825 -0.51714162 0.74440513
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002454351 1.144113831 0.396427805
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90554395 0.60773917 0.90554395 0.87034834 0.82640476 0.62702832
#> [7] 0.34952306 0.54989954 0.45456245 0.26688032 0.03539624 0.23102201
#> [13] 0.20420565 0.95405629 0.99344164 0.87034834 0.70088351 0.94050541
#> [19] 0.84144400 0.56943907 0.76200059 0.55970295 0.64589693 0.93351815
#> [25] 0.47859787 0.95405629 0.74508955 0.30182732 0.78724144 0.64589693
#> [31] 0.78724144 0.39627537 0.78724144 0.58853482 0.89851540 0.86315352
#> [37] 0.31378240 0.64589693 0.39627537 0.97386062 0.97386062 0.77883224
#> [43] 0.70088351 0.53037530 0.07909225 0.82640476 0.85596691 0.03539624
#> [49] 0.60773917 0.50036069 0.87034834 0.72766918 0.81081076 0.77043030
#> [55] 0.09466113 0.09466113 0.63648669 0.14677030 0.58853482 0.17630846
#> [61] 0.46656846 0.31378240 0.33743430 0.97386062 0.87034834 0.14677030
#> [67] 0.44258743 0.69184563 0.51091492 0.96725195 0.67335758 0.25485344
#> [73] 0.34952306 0.94050541 0.51091492 0.91956386 0.84144400 0.53037530
#> [79] 0.73646471 0.39627537 0.81860590 0.56943907 0.68259631 0.34952306
#> [85] 0.26688032 0.23102201 0.01180889 0.91956386 0.06278744 0.34952306
#> [91] 0.17630846 0.75353990 0.09466113 0.26688032 0.09466113 0.21832914
#> [97] 0.39627537 0.47859787 0.71869317 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 10 23 10.1 43 140 106 105 110 179 68 86 36 136
#> 10.53 16.92 10.53 12.10 12.68 16.67 19.75 17.56 18.63 20.62 23.81 21.19 21.83
#> 149 127 43.1 188 187 154 111 57 117 130 93 41 149.1
#> 8.37 3.53 12.10 16.16 9.92 12.63 17.45 14.46 17.46 16.47 10.33 18.02 8.37
#> 18 128 60 130.1 60.1 58 60.2 30 107 56 150 130.2 58.1
#> 15.21 20.35 13.15 16.47 13.15 19.34 13.15 17.43 11.18 12.21 20.33 16.47 19.34
#> 91 91.1 81 188.1 184 164 140.1 37 86.1 23.1 40 43.2 125
#> 5.33 5.33 14.06 16.16 17.77 23.60 12.68 12.52 23.81 16.92 18.00 12.10 15.65
#> 123 13 15 15.1 171 169 30.1 194 8 150.1 166 91.2 43.3
#> 13.00 14.34 22.68 22.68 16.57 22.41 17.43 22.40 18.43 20.33 19.98 5.33 12.10
#> 169.1 97 79 134 77 181 90 105.1 187.1 134.1 52 154.1 184.1
#> 22.41 19.14 16.23 17.81 7.27 16.46 20.94 19.75 9.92 17.81 10.42 12.63 17.77
#> 29 55 14 111.1 85 105.2 68.1 99 24 52.1 168 105.3 194.1
#> 15.45 19.34 12.89 17.45 16.44 19.75 20.62 21.19 23.89 10.42 23.72 19.75 22.40
#> 157 15.2 68.2 15.3 153 55.1 41.1 100 22 135 64 172 95
#> 15.10 22.68 20.62 22.68 21.33 19.34 18.02 16.07 24.00 24.00 24.00 24.00 24.00
#> 44 102 17 147 28 20 198 174 112 87 126 142 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 34 84 67 27 126.1 54 122 135.1 137 54.1 72 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 185 152 33 144 67.1 48 116 75 38 152.1 160 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.2 35 138 80 31 161 162 67.2 103 94.1 7 98 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 135.2 146 95.1 20.1 80.1 75.1 1.3 116.1 44.1 135.3 141 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 142.1 54.2 67.3 103.1 2 109 138.1 131.1 3 12 22.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.4 48.1
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[27]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0001134408 0.9724561705 0.4355241065
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.338319473 0.002156671 -0.042515720
#> grade_iii, Cure model
#> 1.380584938
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 180 14.82 1 37 0 0
#> 155 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 105 19.75 1 60 0 0
#> 127 3.53 1 62 0 1
#> 107 11.18 1 54 1 0
#> 30 17.43 1 78 0 0
#> 123 13.00 1 44 1 0
#> 99 21.19 1 38 0 1
#> 169 22.41 1 46 0 0
#> 99.1 21.19 1 38 0 1
#> 159 10.55 1 50 0 1
#> 30.1 17.43 1 78 0 0
#> 169.1 22.41 1 46 0 0
#> 170 19.54 1 43 0 1
#> 145 10.07 1 65 1 0
#> 181 16.46 1 45 0 1
#> 155.1 13.08 1 26 0 0
#> 4 17.64 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 36 21.19 1 48 0 1
#> 101 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 37 12.52 1 57 1 0
#> 199.1 19.81 1 NA 0 1
#> 52 10.42 1 52 0 1
#> 149 8.37 1 33 1 0
#> 195 11.76 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 105.1 19.75 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 76 19.22 1 54 0 1
#> 70 7.38 1 30 1 0
#> 79 16.23 1 54 1 0
#> 171 16.57 1 41 0 1
#> 164 23.60 1 76 0 1
#> 60 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 69.1 23.23 1 25 0 1
#> 157 15.10 1 47 0 0
#> 57 14.46 1 45 0 1
#> 171.1 16.57 1 41 0 1
#> 199.2 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 70.1 7.38 1 30 1 0
#> 159.1 10.55 1 50 0 1
#> 15 22.68 1 48 0 0
#> 129 23.41 1 53 1 0
#> 179 18.63 1 42 0 0
#> 37.1 12.52 1 57 1 0
#> 59.2 10.16 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 179.1 18.63 1 42 0 0
#> 136 21.83 1 43 0 1
#> 16 8.71 1 71 0 1
#> 6 15.64 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 52.1 10.42 1 52 0 1
#> 77 7.27 1 67 0 1
#> 25 6.32 1 34 1 0
#> 175 21.91 1 43 0 0
#> 52.2 10.42 1 52 0 1
#> 101.1 9.97 1 10 0 1
#> 30.2 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 16.1 8.71 1 71 0 1
#> 188 16.16 1 46 0 1
#> 159.2 10.55 1 50 0 1
#> 78.1 23.88 1 43 0 0
#> 123.1 13.00 1 44 1 0
#> 55 19.34 1 69 0 1
#> 167 15.55 1 56 1 0
#> 42 12.43 1 49 0 1
#> 159.3 10.55 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 194 22.40 1 38 0 1
#> 177 12.53 1 75 0 0
#> 181.1 16.46 1 45 0 1
#> 105.2 19.75 1 60 0 0
#> 49 12.19 1 48 1 0
#> 197 21.60 1 69 1 0
#> 40.1 18.00 1 28 1 0
#> 159.4 10.55 1 50 0 1
#> 155.2 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 90 20.94 1 50 0 1
#> 139 21.49 1 63 1 0
#> 92 22.92 1 47 0 1
#> 43 12.10 1 61 0 1
#> 183 9.24 1 67 1 0
#> 30.3 17.43 1 78 0 0
#> 70.2 7.38 1 30 1 0
#> 14.1 12.89 1 21 0 0
#> 18 15.21 1 49 1 0
#> 145.1 10.07 1 65 1 0
#> 155.3 13.08 1 26 0 0
#> 113.1 22.86 1 34 0 0
#> 171.2 16.57 1 41 0 1
#> 57.1 14.46 1 45 0 1
#> 15.1 22.68 1 48 0 0
#> 26.1 15.77 1 49 0 1
#> 13.1 14.34 1 54 0 1
#> 136.1 21.83 1 43 0 1
#> 172 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 94 24.00 0 51 0 1
#> 161 24.00 0 45 0 0
#> 147 24.00 0 76 1 0
#> 82 24.00 0 34 0 0
#> 84 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 135 24.00 0 58 1 0
#> 35 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 82.1 24.00 0 34 0 0
#> 112 24.00 0 61 0 0
#> 44 24.00 0 56 0 0
#> 28 24.00 0 67 1 0
#> 176 24.00 0 43 0 1
#> 74 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 94.1 24.00 0 51 0 1
#> 9.1 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 178 24.00 0 52 1 0
#> 163 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 160 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 82.2 24.00 0 34 0 0
#> 152 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 9.2 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 174.1 24.00 0 49 1 0
#> 22.1 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 65 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 185 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 161.1 24.00 0 45 0 0
#> 80.1 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 44.1 24.00 0 56 0 0
#> 2 24.00 0 9 0 0
#> 178.1 24.00 0 52 1 0
#> 200.1 24.00 0 64 0 0
#> 72.1 24.00 0 40 0 1
#> 172.2 24.00 0 41 0 0
#> 160.1 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 137 24.00 0 45 1 0
#> 21.1 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 161.2 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 172.3 24.00 0 41 0 0
#> 163.1 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 176.1 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 82.3 24.00 0 34 0 0
#> 135.1 24.00 0 58 1 0
#> 82.4 24.00 0 34 0 0
#> 162 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 162.1 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 7.1 24.00 0 37 1 0
#> 174.2 24.00 0 49 1 0
#> 176.2 24.00 0 43 0 1
#> 109.1 24.00 0 48 0 0
#> 147.1 24.00 0 76 1 0
#> 131.1 24.00 0 66 0 0
#> 22.2 24.00 0 52 1 0
#> 182 24.00 0 35 0 0
#> 84.1 24.00 0 39 0 1
#> 152.1 24.00 0 36 0 1
#> 185.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.338 NA NA NA
#> 2 age, Cure model 0.00216 NA NA NA
#> 3 grade_ii, Cure model -0.0425 NA NA NA
#> 4 grade_iii, Cure model 1.38 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000113 NA NA NA
#> 2 grade_ii, Survival model 0.972 NA NA NA
#> 3 grade_iii, Survival model 0.436 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.338319 0.002157 -0.042516 1.380585
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 241.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.338319473 0.002156671 -0.042515720 1.380584938
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0001134408 0.9724561705 0.4355241065
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.56244908 0.68269556 0.73795319 0.50803413 0.40716824 0.99412351
#> [7] 0.84788643 0.52639287 0.76830402 0.35567262 0.22464442 0.35567262
#> [13] 0.85475257 0.52639287 0.22464442 0.43788212 0.90755106 0.59825591
#> [19] 0.73795319 0.27941108 0.35567262 0.92044650 0.48850942 0.93324377
#> [25] 0.81265675 0.88781176 0.95829210 0.02946071 0.40716824 0.35567262
#> [31] 0.45845045 0.96445712 0.61581219 0.57168725 0.07969378 0.73024467
#> [37] 0.12383107 0.12383107 0.67459741 0.69883904 0.57168725 0.63301798
#> [43] 0.96445712 0.85475257 0.19643107 0.10546583 0.46854390 0.81265675
#> [49] 0.16820264 0.79797862 0.46854390 0.30663095 0.94586995 0.64979205
#> [55] 0.78314165 0.88781176 0.98227293 0.98822761 0.29302250 0.88781176
#> [61] 0.92044650 0.52639287 0.69079331 0.94586995 0.62444790 0.85475257
#> [67] 0.02946071 0.76830402 0.44823210 0.65823344 0.82684421 0.85475257
#> [73] 0.48850942 0.25284394 0.80531798 0.59825591 0.40716824 0.83393476
#> [79] 0.33202635 0.50803413 0.85475257 0.73795319 0.71463763 0.25284394
#> [85] 0.39665633 0.34418694 0.15343680 0.84092670 0.93959216 0.52639287
#> [91] 0.96445712 0.78314165 0.66649874 0.90755106 0.73795319 0.16820264
#> [97] 0.57168725 0.69883904 0.19643107 0.63301798 0.71463763 0.30663095
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 23 180 155 40 105 127 107 30 123 99 169 99.1 159
#> 16.92 14.82 13.08 18.00 19.75 3.53 11.18 17.43 13.00 21.19 22.41 21.19 10.55
#> 30.1 169.1 170 145 181 155.1 66 36 101 108 187 37 52
#> 17.43 22.41 19.54 10.07 16.46 13.08 22.13 21.19 9.97 18.29 9.92 12.52 10.42
#> 149 78 105.1 36.1 76 70 79 171 164 60 69 69.1 157
#> 8.37 23.88 19.75 21.19 19.22 7.38 16.23 16.57 23.60 13.15 23.23 23.23 15.10
#> 57 171.1 26 70.1 159.1 15 129 179 37.1 113 140 179.1 136
#> 14.46 16.57 15.77 7.38 10.55 22.68 23.41 18.63 12.52 22.86 12.68 18.63 21.83
#> 16 6 14 52.1 77 25 175 52.2 101.1 30.2 96 16.1 188
#> 8.71 15.64 12.89 10.42 7.27 6.32 21.91 10.42 9.97 17.43 14.54 8.71 16.16
#> 159.2 78.1 123.1 55 167 42 159.3 108.1 194 177 181.1 105.2 49
#> 10.55 23.88 13.00 19.34 15.55 12.43 10.55 18.29 22.40 12.53 16.46 19.75 12.19
#> 197 40.1 159.4 155.2 13 194.1 90 139 92 43 183 30.3 70.2
#> 21.60 18.00 10.55 13.08 14.34 22.40 20.94 21.49 22.92 12.10 9.24 17.43 7.38
#> 14.1 18 145.1 155.3 113.1 171.2 57.1 15.1 26.1 13.1 136.1 172 191
#> 12.89 15.21 10.07 13.08 22.86 16.57 14.46 22.68 15.77 14.34 21.83 24.00 24.00
#> 94 161 147 82 84 174 9 135 35 21 82.1 112 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 176 74 94.1 9.1 22 178 163 54 160 19 82.2 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 9.2 200 174.1 22.1 141 67 65 131 38 172.1 121 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 80 161.1 80.1 7 44.1 2 178.1 200.1 72.1 172.2 160.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 137 21.1 118 161.2 143 172.3 163.1 102 176.1 142 82.3 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.4 162 71 109 28.1 162.1 112.1 116 7.1 174.2 176.2 109.1 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 22.2 182 84.1 152.1 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[28]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004543698 0.556780121 0.400438286
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93627829 0.01489131 0.15908695
#> grade_iii, Cure model
#> 1.41580796
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 93 10.33 1 52 0 1
#> 69 23.23 1 25 0 1
#> 50 10.02 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 133 14.65 1 57 0 0
#> 101 9.97 1 10 0 1
#> 32 20.90 1 37 1 0
#> 78 23.88 1 43 0 0
#> 79 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 159 10.55 1 50 0 1
#> 128 20.35 1 35 0 1
#> 125 15.65 1 67 1 0
#> 58 19.34 1 39 0 0
#> 68 20.62 1 44 0 0
#> 107 11.18 1 54 1 0
#> 16 8.71 1 71 0 1
#> 78.1 23.88 1 43 0 0
#> 184 17.77 1 38 0 0
#> 125.1 15.65 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 133.1 14.65 1 57 0 0
#> 110 17.56 1 65 0 1
#> 110.1 17.56 1 65 0 1
#> 93.1 10.33 1 52 0 1
#> 41 18.02 1 40 1 0
#> 81 14.06 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 184.1 17.77 1 38 0 0
#> 23 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 129 23.41 1 53 1 0
#> 106 16.67 1 49 1 0
#> 76 19.22 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 159.1 10.55 1 50 0 1
#> 49 12.19 1 48 1 0
#> 79.1 16.23 1 54 1 0
#> 14 12.89 1 21 0 0
#> 49.1 12.19 1 48 1 0
#> 195 11.76 1 NA 1 0
#> 93.2 10.33 1 52 0 1
#> 183 9.24 1 67 1 0
#> 184.2 17.77 1 38 0 0
#> 187 9.92 1 39 1 0
#> 170 19.54 1 43 0 1
#> 194 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 18 15.21 1 49 1 0
#> 110.2 17.56 1 65 0 1
#> 155 13.08 1 26 0 0
#> 43 12.10 1 61 0 1
#> 130 16.47 1 53 0 1
#> 155.1 13.08 1 26 0 0
#> 70 7.38 1 30 1 0
#> 89 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 190.1 20.81 1 42 1 0
#> 189 10.51 1 NA 1 0
#> 68.1 20.62 1 44 0 0
#> 168 23.72 1 70 0 0
#> 5 16.43 1 51 0 1
#> 90 20.94 1 50 0 1
#> 175 21.91 1 43 0 0
#> 32.1 20.90 1 37 1 0
#> 192 16.44 1 31 1 0
#> 139 21.49 1 63 1 0
#> 50.1 10.02 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 55 19.34 1 69 0 1
#> 32.2 20.90 1 37 1 0
#> 166 19.98 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 129.1 23.41 1 53 1 0
#> 93.3 10.33 1 52 0 1
#> 167 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 26 15.77 1 49 0 1
#> 145 10.07 1 65 1 0
#> 170.1 19.54 1 43 0 1
#> 86 23.81 1 58 0 1
#> 125.2 15.65 1 67 1 0
#> 8 18.43 1 32 0 0
#> 159.2 10.55 1 50 0 1
#> 110.3 17.56 1 65 0 1
#> 52 10.42 1 52 0 1
#> 107.1 11.18 1 54 1 0
#> 52.1 10.42 1 52 0 1
#> 92 22.92 1 47 0 1
#> 23.1 16.92 1 61 0 0
#> 10 10.53 1 34 0 0
#> 42 12.43 1 49 0 1
#> 100 16.07 1 60 0 0
#> 164 23.60 1 76 0 1
#> 150 20.33 1 48 0 0
#> 192.1 16.44 1 31 1 0
#> 69.1 23.23 1 25 0 1
#> 171 16.57 1 41 0 1
#> 168.1 23.72 1 70 0 0
#> 96 14.54 1 33 0 1
#> 70.1 7.38 1 30 1 0
#> 58.1 19.34 1 39 0 0
#> 49.2 12.19 1 48 1 0
#> 39.2 15.59 1 37 0 1
#> 77 7.27 1 67 0 1
#> 159.3 10.55 1 50 0 1
#> 51.1 18.23 1 83 0 1
#> 86.1 23.81 1 58 0 1
#> 85 16.44 1 36 0 0
#> 21 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 118 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 71.1 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 38 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 143 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 9 24.00 0 31 1 0
#> 21.2 24.00 0 47 0 0
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 9.1 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 141 24.00 0 44 1 0
#> 9.2 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 17 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 12 24.00 0 63 0 0
#> 146.2 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 22.1 24.00 0 52 1 0
#> 137.1 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 7 24.00 0 37 1 0
#> 119 24.00 0 17 0 0
#> 34.1 24.00 0 36 0 0
#> 161.1 24.00 0 45 0 0
#> 115 24.00 0 NA 1 0
#> 72 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 132 24.00 0 55 0 0
#> 119.1 24.00 0 17 0 0
#> 74 24.00 0 43 0 1
#> 21.3 24.00 0 47 0 0
#> 143.1 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 67.1 24.00 0 25 0 0
#> 2 24.00 0 9 0 0
#> 152 24.00 0 36 0 1
#> 146.3 24.00 0 63 1 0
#> 21.4 24.00 0 47 0 0
#> 152.1 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 33 24.00 0 53 0 0
#> 119.2 24.00 0 17 0 0
#> 84 24.00 0 39 0 1
#> 112 24.00 0 61 0 0
#> 1 24.00 0 23 1 0
#> 118.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 178.2 24.00 0 52 1 0
#> 2.1 24.00 0 9 0 0
#> 121.1 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 131 24.00 0 66 0 0
#> 71.2 24.00 0 51 0 0
#> 121.2 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 118.2 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 54.1 24.00 0 53 1 0
#> 102.1 24.00 0 49 0 0
#> 182 24.00 0 35 0 0
#> 47.2 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 143.2 24.00 0 51 0 0
#> 178.3 24.00 0 52 1 0
#> 33.1 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 71.3 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.936 NA NA NA
#> 2 age, Cure model 0.0149 NA NA NA
#> 3 grade_ii, Cure model 0.159 NA NA NA
#> 4 grade_iii, Cure model 1.42 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00454 NA NA NA
#> 2 grade_ii, Survival model 0.557 NA NA NA
#> 3 grade_iii, Survival model 0.400 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93628 0.01489 0.15909 1.41581
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 245.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93627829 0.01489131 0.15908695 1.41580796
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004543698 0.556780121 0.400438286
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.892124950 0.128155822 0.720460703 0.469665457 0.676826551 0.694210851
#> [7] 0.933800189 0.215632609 0.019555539 0.571006538 0.633303164 0.833150260
#> [13] 0.281855781 0.606969650 0.329556819 0.262873496 0.816073328 0.958839397
#> [19] 0.019555539 0.405034659 0.606969650 0.469665457 0.694210851 0.433056279
#> [25] 0.433056279 0.892124950 0.395576550 0.729203309 0.005958364 0.405034659
#> [31] 0.488190112 0.194222548 0.104998019 0.506886570 0.357558258 0.729203309
#> [37] 0.833150260 0.781714264 0.571006538 0.764128659 0.781714264 0.892124950
#> [43] 0.950518381 0.405034659 0.942176404 0.310741787 0.161201276 0.244136855
#> [49] 0.668112729 0.433056279 0.746643221 0.807423243 0.525579936 0.746643221
#> [55] 0.967154571 0.991800142 0.244136855 0.262873496 0.066422142 0.561883695
#> [61] 0.204980380 0.172192712 0.215632609 0.534877867 0.183310298 0.633303164
#> [67] 0.329556819 0.215632609 0.301051961 0.676826551 0.104998019 0.892124950
#> [73] 0.659353586 0.376683438 0.597947762 0.925391832 0.310741787 0.043711537
#> [79] 0.606969650 0.367103988 0.833150260 0.433056279 0.875220029 0.816073328
#> [85] 0.875220029 0.150015109 0.488190112 0.866696846 0.772931192 0.588899311
#> [91] 0.091542106 0.291422888 0.534877867 0.128155822 0.516253455 0.066422142
#> [97] 0.711695071 0.967154571 0.329556819 0.781714264 0.633303164 0.983566572
#> [103] 0.833150260 0.376683438 0.043711537 0.534877867 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 93 69 57 111 180 133 101 32 78 79 39 159 128
#> 10.33 23.23 14.46 17.45 14.82 14.65 9.97 20.90 23.88 16.23 15.59 10.55 20.35
#> 125 58 68 107 16 78.1 184 125.1 111.1 133.1 110 110.1 93.1
#> 15.65 19.34 20.62 11.18 8.71 23.88 17.77 15.65 17.45 14.65 17.56 17.56 10.33
#> 41 81 24 184.1 23 99 129 106 76 81.1 159.1 49 79.1
#> 18.02 14.06 23.89 17.77 16.92 21.19 23.41 16.67 19.22 14.06 10.55 12.19 16.23
#> 14 49.1 93.2 183 184.2 187 170 194 190 18 110.2 155 43
#> 12.89 12.19 10.33 9.24 17.77 9.92 19.54 22.40 20.81 15.21 17.56 13.08 12.10
#> 130 155.1 70 25 190.1 68.1 168 5 90 175 32.1 192 139
#> 16.47 13.08 7.38 6.32 20.81 20.62 23.72 16.43 20.94 21.91 20.90 16.44 21.49
#> 39.1 55 32.2 166 180.1 129.1 93.3 167 51 26 145 170.1 86
#> 15.59 19.34 20.90 19.98 14.82 23.41 10.33 15.55 18.23 15.77 10.07 19.54 23.81
#> 125.2 8 159.2 110.3 52 107.1 52.1 92 23.1 10 42 100 164
#> 15.65 18.43 10.55 17.56 10.42 11.18 10.42 22.92 16.92 10.53 12.43 16.07 23.60
#> 150 192.1 69.1 171 168.1 96 70.1 58.1 49.2 39.2 77 159.3 51.1
#> 20.33 16.44 23.23 16.57 23.72 14.54 7.38 19.34 12.19 15.59 7.27 10.55 18.23
#> 86.1 85 21 178 82 118 122 22 71 67 161 185 21.1
#> 23.81 16.44 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 156 160 44 38 121 143 196 151 9 21.2 11 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 146.1 102 141 9.2 34 17 191 12 146.2 137 47 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 200 7 119 34.1 161.1 72 53 132 119.1 74 21.3 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 67.1 2 152 146.3 21.4 152.1 54 33 119.2 84 112 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.1 178.2 2.1 121.1 47.1 64 131 71.2 121.2 186 118.2 135 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 182 47.2 144 143.2 178.3 33.1 120 71.3 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[29]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004880639 0.672094154 0.474354249
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.35871672 0.01227582 -0.29434927
#> grade_iii, Cure model
#> 0.44882991
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 50 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 140 12.68 1 59 1 0
#> 124 9.73 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 58 19.34 1 39 0 0
#> 50.1 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 57 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 70.1 7.38 1 30 1 0
#> 192 16.44 1 31 1 0
#> 177 12.53 1 75 0 0
#> 24 23.89 1 38 0 0
#> 177.1 12.53 1 75 0 0
#> 6 15.64 1 39 0 0
#> 10 10.53 1 34 0 0
#> 14 12.89 1 21 0 0
#> 88 18.37 1 47 0 0
#> 145 10.07 1 65 1 0
#> 100 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 56 12.21 1 60 0 0
#> 197 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 169 22.41 1 46 0 0
#> 66 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 90.1 20.94 1 50 0 1
#> 24.1 23.89 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 127 3.53 1 62 0 1
#> 6.1 15.64 1 39 0 0
#> 63 22.77 1 31 1 0
#> 129 23.41 1 53 1 0
#> 43 12.10 1 61 0 1
#> 157 15.10 1 47 0 0
#> 123 13.00 1 44 1 0
#> 60 13.15 1 38 1 0
#> 24.2 23.89 1 38 0 0
#> 169.1 22.41 1 46 0 0
#> 58.1 19.34 1 39 0 0
#> 140.1 12.68 1 59 1 0
#> 169.2 22.41 1 46 0 0
#> 43.1 12.10 1 61 0 1
#> 40 18.00 1 28 1 0
#> 184 17.77 1 38 0 0
#> 26 15.77 1 49 0 1
#> 129.1 23.41 1 53 1 0
#> 149.1 8.37 1 33 1 0
#> 166.1 19.98 1 48 0 0
#> 36 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 192.1 16.44 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 123.1 13.00 1 44 1 0
#> 192.2 16.44 1 31 1 0
#> 114.1 13.68 1 NA 0 0
#> 100.1 16.07 1 60 0 0
#> 175 21.91 1 43 0 0
#> 168 23.72 1 70 0 0
#> 187 9.92 1 39 1 0
#> 99 21.19 1 38 0 1
#> 93 10.33 1 52 0 1
#> 81 14.06 1 34 0 0
#> 45 17.42 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 149.2 8.37 1 33 1 0
#> 175.1 21.91 1 43 0 0
#> 107 11.18 1 54 1 0
#> 181 16.46 1 45 0 1
#> 179 18.63 1 42 0 0
#> 86 23.81 1 58 0 1
#> 52 10.42 1 52 0 1
#> 61 10.12 1 36 0 1
#> 14.1 12.89 1 21 0 0
#> 85 16.44 1 36 0 0
#> 125 15.65 1 67 1 0
#> 29 15.45 1 68 1 0
#> 159 10.55 1 50 0 1
#> 6.2 15.64 1 39 0 0
#> 190.1 20.81 1 42 1 0
#> 171 16.57 1 41 0 1
#> 199.1 19.81 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 5 16.43 1 51 0 1
#> 90.2 20.94 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 169.3 22.41 1 46 0 0
#> 124.1 9.73 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 76.1 19.22 1 54 0 1
#> 129.2 23.41 1 53 1 0
#> 168.1 23.72 1 70 0 0
#> 113 22.86 1 34 0 0
#> 155 13.08 1 26 0 0
#> 159.1 10.55 1 50 0 1
#> 58.2 19.34 1 39 0 0
#> 99.2 21.19 1 38 0 1
#> 125.1 15.65 1 67 1 0
#> 70.2 7.38 1 30 1 0
#> 29.1 15.45 1 68 1 0
#> 5.1 16.43 1 51 0 1
#> 154 12.63 1 20 1 0
#> 66.2 22.13 1 53 0 0
#> 30 17.43 1 78 0 0
#> 149.3 8.37 1 33 1 0
#> 69 23.23 1 25 0 1
#> 140.2 12.68 1 59 1 0
#> 190.2 20.81 1 42 1 0
#> 87 24.00 0 27 0 0
#> 200 24.00 0 64 0 0
#> 38 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 102 24.00 0 49 0 0
#> 104 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 162 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 64.1 24.00 0 43 0 0
#> 144 24.00 0 28 0 1
#> 185 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 87.1 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 104.1 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 198 24.00 0 66 0 1
#> 38.1 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 141 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 115 24.00 0 NA 1 0
#> 182.1 24.00 0 35 0 0
#> 9 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 35 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 132.1 24.00 0 55 0 0
#> 46 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 132.2 24.00 0 55 0 0
#> 2 24.00 0 9 0 0
#> 112 24.00 0 61 0 0
#> 27 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 102.1 24.00 0 49 0 0
#> 142 24.00 0 53 0 0
#> 65.1 24.00 0 57 1 0
#> 141.1 24.00 0 44 1 0
#> 54.1 24.00 0 53 1 0
#> 121.1 24.00 0 57 1 0
#> 147.1 24.00 0 76 1 0
#> 7 24.00 0 37 1 0
#> 162.1 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 109 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 2.1 24.00 0 9 0 0
#> 186 24.00 0 45 1 0
#> 54.2 24.00 0 53 1 0
#> 9.2 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 65.2 24.00 0 57 1 0
#> 141.2 24.00 0 44 1 0
#> 121.2 24.00 0 57 1 0
#> 152.1 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 165 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 87.2 24.00 0 27 0 0
#> 7.1 24.00 0 37 1 0
#> 1 24.00 0 23 1 0
#> 1.1 24.00 0 23 1 0
#> 156.2 24.00 0 50 1 0
#> 162.2 24.00 0 51 0 0
#> 152.2 24.00 0 36 0 1
#> 1.2 24.00 0 23 1 0
#> 22 24.00 0 52 1 0
#> 173.1 24.00 0 19 0 1
#> 160 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.359 NA NA NA
#> 2 age, Cure model 0.0123 NA NA NA
#> 3 grade_ii, Cure model -0.294 NA NA NA
#> 4 grade_iii, Cure model 0.449 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00488 NA NA NA
#> 2 grade_ii, Survival model 0.672 NA NA NA
#> 3 grade_iii, Survival model 0.474 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.35872 0.01228 -0.29435 0.44883
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 255.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.35871672 0.01227582 -0.29434927 0.44882991
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004880639 0.672094154 0.474354249
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.46855825 0.51752761 0.78056427 0.96780205 0.40036991 0.42943359
#> [7] 0.37129196 0.70952224 0.31253034 0.96780205 0.54640806 0.81503262
#> [13] 0.01356508 0.81503262 0.64640054 0.88401704 0.76297011 0.45867099
#> [19] 0.91828613 0.60076412 0.34265937 0.83231897 0.24987333 0.38099916
#> [25] 0.15288908 0.19396669 0.93523326 0.31253034 0.01356508 0.99191030
#> [31] 0.64640054 0.14206052 0.08750005 0.84103058 0.70049724 0.74541541
#> [37] 0.72752311 0.01356508 0.15288908 0.40036991 0.78056427 0.15288908
#> [43] 0.84103058 0.47843058 0.48816073 0.61912027 0.08750005 0.93523326
#> [49] 0.38099916 0.27202803 0.19396669 0.54640806 0.74541541 0.54640806
#> [55] 0.60076412 0.22690940 0.05922424 0.92678367 0.27202803 0.90119586
#> [61] 0.71851406 0.50774791 0.24987333 0.93523326 0.22690940 0.85829484
#> [67] 0.53683303 0.44882723 0.04520809 0.89261665 0.90975496 0.76297011
#> [73] 0.54640806 0.62833092 0.68261045 0.86692679 0.64640054 0.34265937
#> [79] 0.52720820 0.67351044 0.58254929 0.31253034 0.15288908 0.27202803
#> [85] 0.42943359 0.08750005 0.05922424 0.13063771 0.73646279 0.86692679
#> [91] 0.40036991 0.27202803 0.62833092 0.96780205 0.68261045 0.58254929
#> [97] 0.80639955 0.19396669 0.49792382 0.93523326 0.11936612 0.78056427
#> [103] 0.34265937 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 51 106 140 70 58 76 158 57 90 70.1 192 177 24
#> 18.23 16.67 12.68 7.38 19.34 19.22 20.14 14.46 20.94 7.38 16.44 12.53 23.89
#> 177.1 6 10 14 88 145 100 190 56 197 166 169 66
#> 12.53 15.64 10.53 12.89 18.37 10.07 16.07 20.81 12.21 21.60 19.98 22.41 22.13
#> 149 90.1 24.1 127 6.1 63 129 43 157 123 60 24.2 169.1
#> 8.37 20.94 23.89 3.53 15.64 22.77 23.41 12.10 15.10 13.00 13.15 23.89 22.41
#> 58.1 140.1 169.2 43.1 40 184 26 129.1 149.1 166.1 36 66.1 192.1
#> 19.34 12.68 22.41 12.10 18.00 17.77 15.77 23.41 8.37 19.98 21.19 22.13 16.44
#> 123.1 192.2 100.1 175 168 187 99 93 81 45 197.1 149.2 175.1
#> 13.00 16.44 16.07 21.91 23.72 9.92 21.19 10.33 14.06 17.42 21.60 8.37 21.91
#> 107 181 179 86 52 61 14.1 85 125 29 159 6.2 190.1
#> 11.18 16.46 18.63 23.81 10.42 10.12 12.89 16.44 15.65 15.45 10.55 15.64 20.81
#> 171 167 5 90.2 169.3 99.1 76.1 129.2 168.1 113 155 159.1 58.2
#> 16.57 15.55 16.43 20.94 22.41 21.19 19.22 23.41 23.72 22.86 13.08 10.55 19.34
#> 99.2 125.1 70.2 29.1 5.1 154 66.2 30 149.3 69 140.2 190.2 87
#> 21.19 15.65 7.38 15.45 16.43 12.63 22.13 17.43 8.37 23.23 12.68 20.81 24.00
#> 200 38 31 182 102 104 196 64 162 191 65 152 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 144 185 103 87.1 84 104.1 19 132 198 38.1 176 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 173 182.1 9 156 147 35 151 161 132.1 46 121 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.2 2 112 27 98 131 102.1 142 65.1 141.1 54.1 121.1 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 162.1 112.1 109 9.1 156.1 28 2.1 186 54.2 9.2 84.1 65.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 121.2 152.1 83 165 122 87.2 7.1 1 1.1 156.2 162.2 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.2 22 173.1 160 193 146 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[30]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004059177 0.435491643 0.438244467
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.42481313 0.01043790 -0.02532424
#> grade_iii, Cure model
#> 0.46191372
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 125 15.65 1 67 1 0
#> 166 19.98 1 48 0 0
#> 168 23.72 1 70 0 0
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 117 17.46 1 26 0 1
#> 85 16.44 1 36 0 0
#> 51 18.23 1 83 0 1
#> 125.1 15.65 1 67 1 0
#> 179 18.63 1 42 0 0
#> 14 12.89 1 21 0 0
#> 66 22.13 1 53 0 0
#> 108 18.29 1 39 0 1
#> 68 20.62 1 44 0 0
#> 139 21.49 1 63 1 0
#> 63 22.77 1 31 1 0
#> 157.1 15.10 1 47 0 0
#> 85.1 16.44 1 36 0 0
#> 5 16.43 1 51 0 1
#> 49 12.19 1 48 1 0
#> 128 20.35 1 35 0 1
#> 129 23.41 1 53 1 0
#> 24 23.89 1 38 0 0
#> 76 19.22 1 54 0 1
#> 26 15.77 1 49 0 1
#> 56 12.21 1 60 0 0
#> 123 13.00 1 44 1 0
#> 125.2 15.65 1 67 1 0
#> 184 17.77 1 38 0 0
#> 168.1 23.72 1 70 0 0
#> 49.1 12.19 1 48 1 0
#> 6.1 15.64 1 39 0 0
#> 63.1 22.77 1 31 1 0
#> 70 7.38 1 30 1 0
#> 125.3 15.65 1 67 1 0
#> 93 10.33 1 52 0 1
#> 97 19.14 1 65 0 1
#> 99 21.19 1 38 0 1
#> 93.1 10.33 1 52 0 1
#> 29 15.45 1 68 1 0
#> 68.1 20.62 1 44 0 0
#> 169 22.41 1 46 0 0
#> 140 12.68 1 59 1 0
#> 145 10.07 1 65 1 0
#> 181 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 117.1 17.46 1 26 0 1
#> 55 19.34 1 69 0 1
#> 52 10.42 1 52 0 1
#> 41 18.02 1 40 1 0
#> 49.2 12.19 1 48 1 0
#> 97.1 19.14 1 65 0 1
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 155 13.08 1 26 0 0
#> 100 16.07 1 60 0 0
#> 107 11.18 1 54 1 0
#> 153 21.33 1 55 1 0
#> 187.1 9.92 1 39 1 0
#> 63.2 22.77 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 128.1 20.35 1 35 0 1
#> 4 17.64 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 166.1 19.98 1 48 0 0
#> 23 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 52.1 10.42 1 52 0 1
#> 57 14.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 139.1 21.49 1 63 1 0
#> 60 13.15 1 38 1 0
#> 179.1 18.63 1 42 0 0
#> 92 22.92 1 47 0 1
#> 77 7.27 1 67 0 1
#> 157.2 15.10 1 47 0 0
#> 166.2 19.98 1 48 0 0
#> 110 17.56 1 65 0 1
#> 99.1 21.19 1 38 0 1
#> 16 8.71 1 71 0 1
#> 78 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 181.1 16.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 150 20.33 1 48 0 0
#> 4.1 17.64 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 110.1 17.56 1 65 0 1
#> 101.1 9.97 1 10 0 1
#> 177.1 12.53 1 75 0 0
#> 134 17.81 1 47 1 0
#> 199 19.81 1 NA 0 1
#> 140.1 12.68 1 59 1 0
#> 136 21.83 1 43 0 1
#> 166.3 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 164 23.60 1 76 0 1
#> 77.1 7.27 1 67 0 1
#> 50 10.02 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 101.2 9.97 1 10 0 1
#> 113 22.86 1 34 0 0
#> 88 18.37 1 47 0 0
#> 164.1 23.60 1 76 0 1
#> 157.3 15.10 1 47 0 0
#> 93.2 10.33 1 52 0 1
#> 108.1 18.29 1 39 0 1
#> 100.1 16.07 1 60 0 0
#> 200 24.00 0 64 0 0
#> 28 24.00 0 67 1 0
#> 122 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 27 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 138 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 131 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 83 24.00 0 6 0 0
#> 152 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 80 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 146 24.00 0 63 1 0
#> 73 24.00 0 NA 0 1
#> 151 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 27.1 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 122.1 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 98 24.00 0 34 1 0
#> 176 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 71 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 144 24.00 0 28 0 1
#> 20 24.00 0 46 1 0
#> 67 24.00 0 25 0 0
#> 103 24.00 0 56 1 0
#> 2.1 24.00 0 9 0 0
#> 98.1 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 98.2 24.00 0 34 1 0
#> 172 24.00 0 41 0 0
#> 131.1 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 64.1 24.00 0 43 0 0
#> 31 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 144.1 24.00 0 28 0 1
#> 34 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 176.1 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 98.3 24.00 0 34 1 0
#> 27.2 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 11.1 24.00 0 42 0 1
#> 67.1 24.00 0 25 0 0
#> 102.1 24.00 0 49 0 0
#> 2.2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 120.1 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 109 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 163.1 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 65.1 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 116.1 24.00 0 58 0 1
#> 118.1 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 87 24.00 0 27 0 0
#> 172.1 24.00 0 41 0 0
#> 19.1 24.00 0 57 0 1
#> 48.1 24.00 0 31 1 0
#> 31.1 24.00 0 36 0 1
#> 34.1 24.00 0 36 0 0
#> 173.1 24.00 0 19 0 1
#> 87.1 24.00 0 27 0 0
#> 94.1 24.00 0 51 0 1
#> 103.2 24.00 0 56 1 0
#> 67.2 24.00 0 25 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.425 NA NA NA
#> 2 age, Cure model 0.0104 NA NA NA
#> 3 grade_ii, Cure model -0.0253 NA NA NA
#> 4 grade_iii, Cure model 0.462 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00406 NA NA NA
#> 2 grade_ii, Survival model 0.435 NA NA NA
#> 3 grade_iii, Survival model 0.438 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.42481 0.01044 -0.02532 0.46191
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 260.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.42481313 0.01043790 -0.02532424 0.46191372
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004059177 0.435491643 0.438244467
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.667554245 0.632455421 0.297814489 0.027940869 0.694376905 0.596319454
#> [7] 0.587246600 0.505486215 0.559995823 0.440255139 0.632455421 0.383227751
#> [13] 0.783488272 0.149865185 0.421442852 0.240847973 0.181761473 0.110596451
#> [19] 0.694376905 0.559995823 0.578139775 0.836621430 0.260079473 0.075163669
#> [25] 0.004825908 0.354807706 0.623400899 0.827698881 0.774600616 0.632455421
#> [31] 0.477818620 0.027940869 0.836621430 0.667554245 0.110596451 0.974681105
#> [37] 0.632455421 0.889162212 0.364427822 0.211935009 0.889162212 0.685410289
#> [43] 0.240847973 0.139386762 0.792384176 0.915034011 0.541931488 0.402173520
#> [49] 0.231161742 0.505486215 0.345123306 0.871699418 0.449742127 0.836621430
#> [55] 0.364427822 0.949205726 0.729867207 0.765682991 0.605353005 0.862878559
#> [61] 0.201784200 0.949205726 0.110596451 0.260079473 0.523568727 0.297814489
#> [67] 0.532732752 0.809991010 0.871699418 0.738866680 0.160487622 0.181761473
#> [73] 0.756775758 0.383227751 0.087212599 0.983162565 0.694376905 0.297814489
#> [79] 0.487144809 0.211935009 0.966172361 0.015499068 0.335392137 0.541931488
#> [85] 0.923725038 0.278833776 0.459166688 0.487144809 0.923725038 0.809991010
#> [91] 0.468518384 0.792384176 0.171224093 0.297814489 0.747834347 0.052177831
#> [97] 0.983162565 0.278833776 0.923725038 0.098814655 0.411788606 0.052177831
#> [103] 0.694376905 0.889162212 0.421442852 0.605353005 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 6 125 166 168 157 188 79 117 85 51 125.1 179 14
#> 15.64 15.65 19.98 23.72 15.10 16.16 16.23 17.46 16.44 18.23 15.65 18.63 12.89
#> 66 108 68 139 63 157.1 85.1 5 49 128 129 24 76
#> 22.13 18.29 20.62 21.49 22.77 15.10 16.44 16.43 12.19 20.35 23.41 23.89 19.22
#> 26 56 123 125.2 184 168.1 49.1 6.1 63.1 70 125.3 93 97
#> 15.77 12.21 13.00 15.65 17.77 23.72 12.19 15.64 22.77 7.38 15.65 10.33 19.14
#> 99 93.1 29 68.1 169 140 145 181 8 32 117.1 55 52
#> 21.19 10.33 15.45 20.62 22.41 12.68 10.07 16.46 18.43 20.90 17.46 19.34 10.42
#> 41 49.2 97.1 187 96 155 100 107 153 187.1 63.2 128.1 30
#> 18.02 12.19 19.14 9.92 14.54 13.08 16.07 11.18 21.33 9.92 22.77 20.35 17.43
#> 166.1 23 177 52.1 57 175 139.1 60 179.1 92 77 157.2 166.2
#> 19.98 16.92 12.53 10.42 14.46 21.91 21.49 13.15 18.63 22.92 7.27 15.10 19.98
#> 110 99.1 16 78 170 181.1 101 150 40 110.1 101.1 177.1 134
#> 17.56 21.19 8.71 23.88 19.54 16.46 9.97 20.33 18.00 17.56 9.97 12.53 17.81
#> 140.1 136 166.3 13 164 77.1 150.1 101.2 113 88 164.1 157.3 93.2
#> 12.68 21.83 19.98 14.34 23.60 7.27 20.33 9.97 22.86 18.37 23.60 15.10 10.33
#> 108.1 100.1 200 28 122 147 27 126 138 74 44 102 82
#> 18.29 16.07 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 46 83 152 138.1 64 80 53 146 151 198 27.1 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 2 122.1 173 98 176 19 71 80.1 94 144 20 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 2.1 98.1 116 98.2 172 131.1 11 64.1 31 186 144.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 146.1 176.1 142 98.3 27.2 118 11.1 67.1 102.1 2.2 120.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 103.1 109 95 54 163.1 33 65.1 135 116.1 118.1 46.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 19.1 48.1 31.1 34.1 173.1 87.1 94.1 103.2 67.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[31]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007285151 0.508610979 0.482975902
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.377323032 -0.004390979 -0.523307569
#> grade_iii, Cure model
#> 0.430746911
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 199 19.81 1 NA 0 1
#> 5 16.43 1 51 0 1
#> 5.1 16.43 1 51 0 1
#> 88 18.37 1 47 0 0
#> 105 19.75 1 60 0 0
#> 69 23.23 1 25 0 1
#> 14 12.89 1 21 0 0
#> 60 13.15 1 38 1 0
#> 58 19.34 1 39 0 0
#> 128.1 20.35 1 35 0 1
#> 93 10.33 1 52 0 1
#> 134 17.81 1 47 1 0
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 13 14.34 1 54 0 1
#> 93.1 10.33 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 168 23.72 1 70 0 0
#> 66 22.13 1 53 0 0
#> 23 16.92 1 61 0 0
#> 8 18.43 1 32 0 0
#> 25 6.32 1 34 1 0
#> 26 15.77 1 49 0 1
#> 15 22.68 1 48 0 0
#> 76 19.22 1 54 0 1
#> 89.1 11.44 1 NA 0 0
#> 124 9.73 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 77 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 99 21.19 1 38 0 1
#> 68 20.62 1 44 0 0
#> 159 10.55 1 50 0 1
#> 10 10.53 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 179 18.63 1 42 0 0
#> 59 10.16 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 117 17.46 1 26 0 1
#> 32 20.90 1 37 1 0
#> 111 17.45 1 47 0 1
#> 85 16.44 1 36 0 0
#> 97 19.14 1 65 0 1
#> 123 13.00 1 44 1 0
#> 108 18.29 1 39 0 1
#> 107 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 107.1 11.18 1 54 1 0
#> 157 15.10 1 47 0 0
#> 149 8.37 1 33 1 0
#> 158 20.14 1 74 1 0
#> 14.1 12.89 1 21 0 0
#> 159.1 10.55 1 50 0 1
#> 175 21.91 1 43 0 0
#> 50 10.02 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 29 15.45 1 68 1 0
#> 166 19.98 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 113.1 22.86 1 34 0 0
#> 111.1 17.45 1 47 0 1
#> 18 15.21 1 49 1 0
#> 89.2 11.44 1 NA 0 0
#> 166.1 19.98 1 48 0 0
#> 14.2 12.89 1 21 0 0
#> 32.1 20.90 1 37 1 0
#> 184.2 17.77 1 38 0 0
#> 50.1 10.02 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 42 12.43 1 49 0 1
#> 6 15.64 1 39 0 0
#> 52 10.42 1 52 0 1
#> 130 16.47 1 53 0 1
#> 88.1 18.37 1 47 0 0
#> 25.1 6.32 1 34 1 0
#> 100 16.07 1 60 0 0
#> 113.2 22.86 1 34 0 0
#> 181 16.46 1 45 0 1
#> 159.2 10.55 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 70 7.38 1 30 1 0
#> 166.2 19.98 1 48 0 0
#> 43.2 12.10 1 61 0 1
#> 136 21.83 1 43 0 1
#> 16 8.71 1 71 0 1
#> 158.1 20.14 1 74 1 0
#> 188 16.16 1 46 0 1
#> 59.1 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 81 14.06 1 34 0 0
#> 108.1 18.29 1 39 0 1
#> 85.1 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 78 23.88 1 43 0 0
#> 23.1 16.92 1 61 0 0
#> 136.1 21.83 1 43 0 1
#> 128.2 20.35 1 35 0 1
#> 181.1 16.46 1 45 0 1
#> 89.3 11.44 1 NA 0 0
#> 166.3 19.98 1 48 0 0
#> 108.2 18.29 1 39 0 1
#> 179.1 18.63 1 42 0 0
#> 117.1 17.46 1 26 0 1
#> 167 15.55 1 56 1 0
#> 177 12.53 1 75 0 0
#> 136.2 21.83 1 43 0 1
#> 140 12.68 1 59 1 0
#> 194 22.40 1 38 0 1
#> 60.1 13.15 1 38 1 0
#> 117.2 17.46 1 26 0 1
#> 20 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 116 24.00 0 58 0 1
#> 103 24.00 0 56 1 0
#> 115 24.00 0 NA 1 0
#> 126 24.00 0 48 0 0
#> 103.1 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 115.1 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 178.1 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 182 24.00 0 35 0 0
#> 98 24.00 0 34 1 0
#> 191 24.00 0 60 0 1
#> 47.1 24.00 0 38 0 1
#> 20.1 24.00 0 46 1 0
#> 118 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 44 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 46.1 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 47.2 24.00 0 38 0 1
#> 118.1 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 47.3 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 126.1 24.00 0 48 0 0
#> 103.2 24.00 0 56 1 0
#> 94 24.00 0 51 0 1
#> 67 24.00 0 25 0 0
#> 148.1 24.00 0 61 1 0
#> 131 24.00 0 66 0 0
#> 1.1 24.00 0 23 1 0
#> 17 24.00 0 38 0 1
#> 17.1 24.00 0 38 0 1
#> 182.1 24.00 0 35 0 0
#> 21 24.00 0 47 0 0
#> 131.1 24.00 0 66 0 0
#> 75.1 24.00 0 21 1 0
#> 156.1 24.00 0 50 1 0
#> 119 24.00 0 17 0 0
#> 94.1 24.00 0 51 0 1
#> 116.1 24.00 0 58 0 1
#> 47.4 24.00 0 38 0 1
#> 131.2 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 172.1 24.00 0 41 0 0
#> 80 24.00 0 41 0 0
#> 116.2 24.00 0 58 0 1
#> 17.2 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 17.3 24.00 0 38 0 1
#> 191.1 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 67.1 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 75.2 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 193 24.00 0 45 0 1
#> 98.1 24.00 0 34 1 0
#> 182.2 24.00 0 35 0 0
#> 34 24.00 0 36 0 0
#> 20.2 24.00 0 46 1 0
#> 44.1 24.00 0 56 0 0
#> 121 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 126.2 24.00 0 48 0 0
#> 94.2 24.00 0 51 0 1
#> 174 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 116.3 24.00 0 58 0 1
#> 147 24.00 0 76 1 0
#> 46.2 24.00 0 71 0 0
#> 80.1 24.00 0 41 0 0
#> 148.2 24.00 0 61 1 0
#> 144 24.00 0 28 0 1
#> 115.2 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.377 NA NA NA
#> 2 age, Cure model -0.00439 NA NA NA
#> 3 grade_ii, Cure model -0.523 NA NA NA
#> 4 grade_iii, Cure model 0.431 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00729 NA NA NA
#> 2 grade_ii, Survival model 0.509 NA NA NA
#> 3 grade_iii, Survival model 0.483 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.377323 -0.004391 -0.523308 0.430747
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 253.7
#> Residual Deviance: 247.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.377323032 -0.004390979 -0.523307569 0.430746911
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007285151 0.508610979 0.482975902
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.43533571 0.76085410 0.76085410 0.60309178 0.53291246 0.16464494
#> [7] 0.86294234 0.84487466 0.54222317 0.43533571 0.95341911 0.64354765
#> [13] 0.89839874 0.89839874 0.83254038 0.95341911 0.18838377 0.09865279
#> [19] 0.28457944 0.71153922 0.59459157 0.98480628 0.78772042 0.24585201
#> [25] 0.55148164 0.37596127 0.97965967 0.79431762 0.37596127 0.42376341
#> [31] 0.92639617 0.94260824 0.57764955 0.99495304 0.67455593 0.40070018
#> [37] 0.69693916 0.74702961 0.56902429 0.85694202 0.61978168 0.91529664
#> [43] 0.65143723 0.91529664 0.82630200 0.96924721 0.47702641 0.86294234
#> [49] 0.92639617 0.30259020 0.65143723 0.81372025 0.49629283 0.18838377
#> [55] 0.69693916 0.82004434 0.49629283 0.86294234 0.40070018 0.65143723
#> [61] 0.13718107 0.89256161 0.80082248 0.94803475 0.72597356 0.60309178
#> [67] 0.98480628 0.78104968 0.18838377 0.73312799 0.92639617 0.55148164
#> [73] 0.97446831 0.49629283 0.89839874 0.32021543 0.96399456 0.47702641
#> [79] 0.77434756 0.36226479 0.83871389 0.61978168 0.74702961 0.46649881
#> [85] 0.04749136 0.71153922 0.32021543 0.43533571 0.73312799 0.49629283
#> [91] 0.61978168 0.57764955 0.67455593 0.80731002 0.88667380 0.32021543
#> [97] 0.88075743 0.26601562 0.84487466 0.67455593 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 128 5 5.1 88 105 69 14 60 58 128.1 93 134 43
#> 20.35 16.43 16.43 18.37 19.75 23.23 12.89 13.15 19.34 20.35 10.33 17.81 12.10
#> 43.1 13 93.1 113 168 66 23 8 25 26 15 76 36
#> 12.10 14.34 10.33 22.86 23.72 22.13 16.92 18.43 6.32 15.77 22.68 19.22 21.19
#> 77 125 99 68 159 10 179 91 117 32 111 85 97
#> 7.27 15.65 21.19 20.62 10.55 10.53 18.63 5.33 17.46 20.90 17.45 16.44 19.14
#> 123 108 107 184 107.1 157 149 158 14.1 159.1 175 184.1 29
#> 13.00 18.29 11.18 17.77 11.18 15.10 8.37 20.14 12.89 10.55 21.91 17.77 15.45
#> 166 113.1 111.1 18 166.1 14.2 32.1 184.2 129 42 6 52 130
#> 19.98 22.86 17.45 15.21 19.98 12.89 20.90 17.77 23.41 12.43 15.64 10.42 16.47
#> 88.1 25.1 100 113.2 181 159.2 76.1 70 166.2 43.2 136 16 158.1
#> 18.37 6.32 16.07 22.86 16.46 10.55 19.22 7.38 19.98 12.10 21.83 8.71 20.14
#> 188 139 81 108.1 85.1 150 78 23.1 136.1 128.2 181.1 166.3 108.2
#> 16.16 21.49 14.06 18.29 16.44 20.33 23.88 16.92 21.83 20.35 16.46 19.98 18.29
#> 179.1 117.1 167 177 136.2 140 194 60.1 117.2 20 178 156 33
#> 18.63 17.46 15.55 12.53 21.83 12.68 22.40 13.15 17.46 24.00 24.00 24.00 24.00
#> 151 116 103 126 103.1 47 148 178.1 112 182 98 191 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 118 28 44 46 143 1 46.1 172 47.2 118.1 75 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 47.3 95 126.1 103.2 94 67 148.1 131 1.1 17 17.1 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 131.1 75.1 156.1 119 94.1 116.1 47.4 131.2 12 172.1 80 116.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 104 17.3 191.1 132 67.1 162 152 75.2 87 193 98.1 182.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 20.2 44.1 121 141 126.2 94.2 174 138 116.3 147 46.2 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.2 144
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[32]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0007723874 0.2938851078 0.2276429621
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.71017073 0.01539254 0.09334648
#> grade_iii, Cure model
#> 0.40750850
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 30 17.43 1 78 0 0
#> 129 23.41 1 53 1 0
#> 70 7.38 1 30 1 0
#> 76 19.22 1 54 0 1
#> 52 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 85 16.44 1 36 0 0
#> 81 14.06 1 34 0 0
#> 15 22.68 1 48 0 0
#> 177 12.53 1 75 0 0
#> 169 22.41 1 46 0 0
#> 43 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 58 19.34 1 39 0 0
#> 18 15.21 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 167 15.55 1 56 1 0
#> 29 15.45 1 68 1 0
#> 101 9.97 1 10 0 1
#> 50.1 10.02 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 24 23.89 1 38 0 0
#> 139 21.49 1 63 1 0
#> 179 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 145 10.07 1 65 1 0
#> 99 21.19 1 38 0 1
#> 183 9.24 1 67 1 0
#> 140 12.68 1 59 1 0
#> 60 13.15 1 38 1 0
#> 124 9.73 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 36 21.19 1 48 0 1
#> 149 8.37 1 33 1 0
#> 128 20.35 1 35 0 1
#> 105 19.75 1 60 0 0
#> 81.1 14.06 1 34 0 0
#> 124.1 9.73 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 181 16.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 184.1 17.77 1 38 0 0
#> 157 15.10 1 47 0 0
#> 97 19.14 1 65 0 1
#> 81.2 14.06 1 34 0 0
#> 129.1 23.41 1 53 1 0
#> 45.1 17.42 1 54 0 1
#> 139.1 21.49 1 63 1 0
#> 154 12.63 1 20 1 0
#> 127 3.53 1 62 0 1
#> 179.1 18.63 1 42 0 0
#> 76.1 19.22 1 54 0 1
#> 100 16.07 1 60 0 0
#> 168 23.72 1 70 0 0
#> 184.2 17.77 1 38 0 0
#> 105.1 19.75 1 60 0 0
#> 63.1 22.77 1 31 1 0
#> 10 10.53 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 110 17.56 1 65 0 1
#> 45.2 17.42 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 106.1 16.67 1 49 1 0
#> 195 11.76 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 40 18.00 1 28 1 0
#> 139.2 21.49 1 63 1 0
#> 59 10.16 1 NA 1 0
#> 128.1 20.35 1 35 0 1
#> 5 16.43 1 51 0 1
#> 86.1 23.81 1 58 0 1
#> 149.1 8.37 1 33 1 0
#> 30.1 17.43 1 78 0 0
#> 134 17.81 1 47 1 0
#> 40.1 18.00 1 28 1 0
#> 157.1 15.10 1 47 0 0
#> 77 7.27 1 67 0 1
#> 32 20.90 1 37 1 0
#> 42 12.43 1 49 0 1
#> 195.1 11.76 1 NA 1 0
#> 149.2 8.37 1 33 1 0
#> 92 22.92 1 47 0 1
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 29.1 15.45 1 68 1 0
#> 170 19.54 1 43 0 1
#> 63.2 22.77 1 31 1 0
#> 113.1 22.86 1 34 0 0
#> 18.1 15.21 1 49 1 0
#> 66 22.13 1 53 0 0
#> 177.1 12.53 1 75 0 0
#> 166.1 19.98 1 48 0 0
#> 23 16.92 1 61 0 0
#> 26 15.77 1 49 0 1
#> 52.2 10.42 1 52 0 1
#> 153 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 108 18.29 1 39 0 1
#> 79 16.23 1 54 1 0
#> 123 13.00 1 44 1 0
#> 189 10.51 1 NA 1 0
#> 149.3 8.37 1 33 1 0
#> 97.1 19.14 1 65 0 1
#> 18.2 15.21 1 49 1 0
#> 111 17.45 1 47 0 1
#> 171 16.57 1 41 0 1
#> 113.2 22.86 1 34 0 0
#> 195.2 11.76 1 NA 1 0
#> 50.2 10.02 1 NA 1 0
#> 135 24.00 0 58 1 0
#> 182 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 65 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 135.1 24.00 0 58 1 0
#> 47 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 27.1 24.00 0 63 1 0
#> 62.1 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 104 24.00 0 50 1 0
#> 2.1 24.00 0 9 0 0
#> 98 24.00 0 34 1 0
#> 11 24.00 0 42 0 1
#> 102 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 118.1 24.00 0 44 1 0
#> 143.1 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 116 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 115 24.00 0 NA 1 0
#> 186 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 148 24.00 0 61 1 0
#> 200 24.00 0 64 0 0
#> 47.2 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 152 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 67 24.00 0 25 0 0
#> 115.1 24.00 0 NA 1 0
#> 83 24.00 0 6 0 0
#> 12 24.00 0 63 0 0
#> 147 24.00 0 76 1 0
#> 142 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 144 24.00 0 28 0 1
#> 3 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 33.1 24.00 0 53 0 0
#> 152.1 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 104.1 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 64 24.00 0 43 0 0
#> 22 24.00 0 52 1 0
#> 178 24.00 0 52 1 0
#> 178.1 24.00 0 52 1 0
#> 115.2 24.00 0 NA 1 0
#> 178.2 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 162 24.00 0 51 0 0
#> 20.1 24.00 0 46 1 0
#> 182.1 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 143.2 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 173.2 24.00 0 19 0 1
#> 151 24.00 0 42 0 0
#> 104.2 24.00 0 50 1 0
#> 67.1 24.00 0 25 0 0
#> 47.3 24.00 0 38 0 1
#> 102.1 24.00 0 49 0 0
#> 182.2 24.00 0 35 0 0
#> 174 24.00 0 49 1 0
#> 46 24.00 0 71 0 0
#> 22.1 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 174.1 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 72 24.00 0 40 0 1
#> 120 24.00 0 68 0 1
#> 33.2 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.710 NA NA NA
#> 2 age, Cure model 0.0154 NA NA NA
#> 3 grade_ii, Cure model 0.0933 NA NA NA
#> 4 grade_iii, Cure model 0.408 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000772 NA NA NA
#> 2 grade_ii, Survival model 0.294 NA NA NA
#> 3 grade_iii, Survival model 0.228 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71017 0.01539 0.09335 0.40751
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 252.5
#> Residual Deviance: 249 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71017073 0.01539254 0.09334648 0.40750850
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0007723874 0.2938851078 0.2276429621
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.55149026 0.08887800 0.96766969 0.40654687 0.87757384 0.04159574
#> [7] 0.65256365 0.76683172 0.20172427 0.83530835 0.21391009 0.86068715
#> [13] 0.16725755 0.39631437 0.72390491 0.87757384 0.69753027 0.70641944
#> [19] 0.91077369 0.57024135 0.01575128 0.23820489 0.44605784 0.50425463
#> [25] 0.90243954 0.28202509 0.91908766 0.81826134 0.79249579 0.33489351
#> [31] 0.28202509 0.93551821 0.31416983 0.36570547 0.76683172 0.12995646
#> [37] 0.64349830 0.34528350 0.50425463 0.74961009 0.42644880 0.76683172
#> [43] 0.08887800 0.57024135 0.23820489 0.82680077 0.99194893 0.44605784
#> [49] 0.40654687 0.67962526 0.07188200 0.50425463 0.36570547 0.16725755
#> [55] 0.86913159 0.60701706 0.53248641 0.57024135 0.91908766 0.60701706
#> [61] 0.80968574 0.47547276 0.23820489 0.31416983 0.66162546 0.04159574
#> [67] 0.93551821 0.55149026 0.49464655 0.47547276 0.74961009 0.97578423
#> [73] 0.30342238 0.85221643 0.93551821 0.11601050 0.63439446 0.70641944
#> [79] 0.38607379 0.16725755 0.12995646 0.72390491 0.22607104 0.83530835
#> [85] 0.34528350 0.59772032 0.68859546 0.87757384 0.27085838 0.98387708
#> [91] 0.46563865 0.67064944 0.80110865 0.93551821 0.42644880 0.72390491
#> [97] 0.54201349 0.62525020 0.12995646 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 30 129 70 76 52 86 85 81 15 177 169 43 63
#> 17.43 23.41 7.38 19.22 10.42 23.81 16.44 14.06 22.68 12.53 22.41 12.10 22.77
#> 58 18 52.1 167 29 101 45 24 139 179 184 145 99
#> 19.34 15.21 10.42 15.55 15.45 9.97 17.42 23.89 21.49 18.63 17.77 10.07 21.19
#> 183 140 60 158 36 149 128 105 81.1 113 181 166 184.1
#> 9.24 12.68 13.15 20.14 21.19 8.37 20.35 19.75 14.06 22.86 16.46 19.98 17.77
#> 157 97 81.2 129.1 45.1 139.1 154 127 179.1 76.1 100 168 184.2
#> 15.10 19.14 14.06 23.41 17.42 21.49 12.63 3.53 18.63 19.22 16.07 23.72 17.77
#> 105.1 63.1 10 106 110 45.2 183.1 106.1 14 40 139.2 128.1 5
#> 19.75 22.77 10.53 16.67 17.56 17.42 9.24 16.67 12.89 18.00 21.49 20.35 16.43
#> 86.1 149.1 30.1 134 40.1 157.1 77 32 42 149.2 92 130 29.1
#> 23.81 8.37 17.43 17.81 18.00 15.10 7.27 20.90 12.43 8.37 22.92 16.47 15.45
#> 170 63.2 113.1 18.1 66 177.1 166.1 23 26 52.2 153 91 108
#> 19.54 22.77 22.86 15.21 22.13 12.53 19.98 16.92 15.77 10.42 21.33 5.33 18.29
#> 79 123 149.3 97.1 18.2 111 171 113.2 135 182 80 156 196
#> 16.23 13.00 8.37 19.14 15.21 17.45 16.57 22.86 24.00 24.00 24.00 24.00 24.00
#> 65 118 143 135.1 47 48 27 62 1 27.1 62.1 2 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 98 11 102 54 118.1 143.1 47.1 75 116 198 186 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 47.2 20 152 33 193 67 83 12 147 142 141 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 3 112 33.1 152.1 95 104.1 165 84 64 22 178 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.2 94 162 20.1 182.1 173 143.2 35 173.1 173.2 151 104.2 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.3 102.1 182.2 174 46 22.1 141.1 193.1 174.1 34 72 120 33.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[33]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009071933 0.412462807 0.143630154
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.39071083 0.01266084 -0.54977507
#> grade_iii, Cure model
#> 0.63116242
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 154 12.63 1 20 1 0
#> 56 12.21 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 177 12.53 1 75 0 0
#> 134.1 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 93 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 77 7.27 1 67 0 1
#> 92 22.92 1 47 0 1
#> 136 21.83 1 43 0 1
#> 157.1 15.10 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 77.1 7.27 1 67 0 1
#> 183 9.24 1 67 1 0
#> 105 19.75 1 60 0 0
#> 145 10.07 1 65 1 0
#> 85 16.44 1 36 0 0
#> 55 19.34 1 69 0 1
#> 153 21.33 1 55 1 0
#> 58 19.34 1 39 0 0
#> 61 10.12 1 36 0 1
#> 30 17.43 1 78 0 0
#> 69 23.23 1 25 0 1
#> 56.1 12.21 1 60 0 0
#> 139 21.49 1 63 1 0
#> 108 18.29 1 39 0 1
#> 30.1 17.43 1 78 0 0
#> 129 23.41 1 53 1 0
#> 59 10.16 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 16 8.71 1 71 0 1
#> 188 16.16 1 46 0 1
#> 86 23.81 1 58 0 1
#> 180 14.82 1 37 0 0
#> 90 20.94 1 50 0 1
#> 169 22.41 1 46 0 0
#> 32 20.90 1 37 1 0
#> 113 22.86 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 134.2 17.81 1 47 1 0
#> 107 11.18 1 54 1 0
#> 134.3 17.81 1 47 1 0
#> 117 17.46 1 26 0 1
#> 113.1 22.86 1 34 0 0
#> 194 22.40 1 38 0 1
#> 179 18.63 1 42 0 0
#> 41 18.02 1 40 1 0
#> 110 17.56 1 65 0 1
#> 68 20.62 1 44 0 0
#> 150 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 199 19.81 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 175.1 21.91 1 43 0 0
#> 13 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 24 23.89 1 38 0 0
#> 154.1 12.63 1 20 1 0
#> 90.1 20.94 1 50 0 1
#> 10 10.53 1 34 0 0
#> 159.1 10.55 1 50 0 1
#> 127 3.53 1 62 0 1
#> 37.1 12.52 1 57 1 0
#> 88 18.37 1 47 0 0
#> 86.1 23.81 1 58 0 1
#> 37.2 12.52 1 57 1 0
#> 188.1 16.16 1 46 0 1
#> 187 9.92 1 39 1 0
#> 179.1 18.63 1 42 0 0
#> 16.1 8.71 1 71 0 1
#> 45 17.42 1 54 0 1
#> 175.2 21.91 1 43 0 0
#> 197 21.60 1 69 1 0
#> 26.1 15.77 1 49 0 1
#> 90.2 20.94 1 50 0 1
#> 181 16.46 1 45 0 1
#> 37.3 12.52 1 57 1 0
#> 15 22.68 1 48 0 0
#> 157.2 15.10 1 47 0 0
#> 58.1 19.34 1 39 0 0
#> 145.1 10.07 1 65 1 0
#> 158 20.14 1 74 1 0
#> 79 16.23 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 58.2 19.34 1 39 0 0
#> 97 19.14 1 65 0 1
#> 127.1 3.53 1 62 0 1
#> 149 8.37 1 33 1 0
#> 30.2 17.43 1 78 0 0
#> 190 20.81 1 42 1 0
#> 60.1 13.15 1 38 1 0
#> 10.1 10.53 1 34 0 0
#> 60.2 13.15 1 38 1 0
#> 50 10.02 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 51.1 18.23 1 83 0 1
#> 93.1 10.33 1 52 0 1
#> 153.1 21.33 1 55 1 0
#> 134.4 17.81 1 47 1 0
#> 124 9.73 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 15.1 22.68 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 179.2 18.63 1 42 0 0
#> 87 24.00 0 27 0 0
#> 148 24.00 0 61 1 0
#> 173 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 146 24.00 0 63 1 0
#> 75 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 118 24.00 0 44 1 0
#> 185.1 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 22.2 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 48 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 146.1 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 67 24.00 0 25 0 0
#> 53 24.00 0 32 0 1
#> 147.1 24.00 0 76 1 0
#> 141 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 3.1 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 196 24.00 0 19 0 0
#> 198 24.00 0 66 0 1
#> 48.1 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 146.2 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 94 24.00 0 51 0 1
#> 162.1 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 132.1 24.00 0 55 0 0
#> 9.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 176.1 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 116.1 24.00 0 58 0 1
#> 19.1 24.00 0 57 0 1
#> 131.1 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 137 24.00 0 45 1 0
#> 65.1 24.00 0 57 1 0
#> 7.1 24.00 0 37 1 0
#> 44 24.00 0 56 0 0
#> 103.1 24.00 0 56 1 0
#> 148.1 24.00 0 61 1 0
#> 65.2 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 156.1 24.00 0 50 1 0
#> 144 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 115 24.00 0 NA 1 0
#> 75.1 24.00 0 21 1 0
#> 148.2 24.00 0 61 1 0
#> 104 24.00 0 50 1 0
#> 44.1 24.00 0 56 0 0
#> 182 24.00 0 35 0 0
#> 163 24.00 0 66 0 0
#> 162.2 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 198.1 24.00 0 66 0 1
#> 34 24.00 0 36 0 0
#> 3.2 24.00 0 31 1 0
#> 132.2 24.00 0 55 0 0
#> 119 24.00 0 17 0 0
#> 156.2 24.00 0 50 1 0
#> 94.1 24.00 0 51 0 1
#> 33 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 27.1 24.00 0 63 1 0
#> 137.1 24.00 0 45 1 0
#> 160.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.391 NA NA NA
#> 2 age, Cure model 0.0127 NA NA NA
#> 3 grade_ii, Cure model -0.550 NA NA NA
#> 4 grade_iii, Cure model 0.631 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00907 NA NA NA
#> 2 grade_ii, Survival model 0.412 NA NA NA
#> 3 grade_iii, Survival model 0.144 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.39071 0.01266 -0.54978 0.63116
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 250.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.39071083 0.01266084 -0.54977507 0.63116242
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009071933 0.412462807 0.143630154
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.65576271 0.50266351 0.84083655 0.88166005 0.33061500 0.77215498
#> [7] 0.85287653 0.65576271 0.78496962 0.92089721 0.81648350 0.97966184
#> [13] 0.19983155 0.37104834 0.78496962 0.97966184 0.95879269 0.53104639
#> [19] 0.93736294 0.74586765 0.54014118 0.40964541 0.54014118 0.93187649
#> [25] 0.70518058 0.17927240 0.88166005 0.39749308 0.61604887 0.70518058
#> [31] 0.15760326 0.64800155 0.96407563 0.75916777 0.10821204 0.80386790
#> [37] 0.44265475 0.28532293 0.47298754 0.21888733 0.65576271 0.89301953
#> [43] 0.65576271 0.69810078 0.21888733 0.30133842 0.58283411 0.64015131
#> [49] 0.69098769 0.49291811 0.51229946 0.89866466 0.85887649 0.33061500
#> [55] 0.81019741 0.73238961 0.05328653 0.84083655 0.44265475 0.90980547
#> [61] 0.89866466 0.98988451 0.85887649 0.60770440 0.10821204 0.85887649
#> [67] 0.75916777 0.95345760 0.58283411 0.96407563 0.72558151 0.33061500
#> [73] 0.38468490 0.77215498 0.44265475 0.73915125 0.85887649 0.25328732
#> [79] 0.78496962 0.54014118 0.93736294 0.52183752 0.75256076 0.54014118
#> [85] 0.57425094 0.98988451 0.97447633 0.70518058 0.48307728 0.81648350
#> [91] 0.90980547 0.81648350 0.62432112 0.62432112 0.92089721 0.40964541
#> [97] 0.65576271 0.94808791 0.25328732 0.30133842 0.83472361 0.43167461
#> [103] 0.58283411 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 134 128 154 56 175 26 177 134.1 157 93 60 77 92
#> 17.81 20.35 12.63 12.21 21.91 15.77 12.53 17.81 15.10 10.33 13.15 7.27 22.92
#> 136 157.1 77.1 183 105 145 85 55 153 58 61 30 69
#> 21.83 15.10 7.27 9.24 19.75 10.07 16.44 19.34 21.33 19.34 10.12 17.43 23.23
#> 56.1 139 108 30.1 129 40 16 188 86 180 90 169 32
#> 12.21 21.49 18.29 17.43 23.41 18.00 8.71 16.16 23.81 14.82 20.94 22.41 20.90
#> 113 134.2 107 134.3 117 113.1 194 179 41 110 68 150 159
#> 22.86 17.81 11.18 17.81 17.46 22.86 22.40 18.63 18.02 17.56 20.62 20.33 10.55
#> 37 175.1 13 23 24 154.1 90.1 10 159.1 127 37.1 88 86.1
#> 12.52 21.91 14.34 16.92 23.89 12.63 20.94 10.53 10.55 3.53 12.52 18.37 23.81
#> 37.2 188.1 187 179.1 16.1 45 175.2 197 26.1 90.2 181 37.3 15
#> 12.52 16.16 9.92 18.63 8.71 17.42 21.91 21.60 15.77 20.94 16.46 12.52 22.68
#> 157.2 58.1 145.1 158 79 58.2 97 127.1 149 30.2 190 60.1 10.1
#> 15.10 19.34 10.07 20.14 16.23 19.34 19.14 3.53 8.37 17.43 20.81 13.15 10.53
#> 60.2 51 51.1 93.1 153.1 134.4 101 15.1 194.1 155 99 179.2 87
#> 13.15 18.23 18.23 10.33 21.33 17.81 9.97 22.68 22.40 13.08 21.19 18.63 24.00
#> 148 173 3 132 9 47 162 160 147 146 75 143 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 22.1 71 83 118 185.1 27 142 22.2 176 48 116 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 67 53 147.1 141 121 131 102 3.1 151 196 198 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 146.2 19 94 162.1 7 132.1 9.1 65 176.1 156 116.1 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 103 137 65.1 7.1 44 103.1 148.1 65.2 82 156.1 144 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 148.2 104 44.1 182 163 162.2 87.1 198.1 34 3.2 132.2 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 94.1 33 17 172 27.1 137.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[34]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02035701 0.54281160 0.31950918
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.5820936321 0.0098211072 0.0006808059
#> grade_iii, Cure model
#> 0.7836287588
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 164 23.60 1 76 0 1
#> 127 3.53 1 62 0 1
#> 149 8.37 1 33 1 0
#> 55 19.34 1 69 0 1
#> 6 15.64 1 39 0 0
#> 168 23.72 1 70 0 0
#> 25 6.32 1 34 1 0
#> 51 18.23 1 83 0 1
#> 150 20.33 1 48 0 0
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 181 16.46 1 45 0 1
#> 81 14.06 1 34 0 0
#> 52 10.42 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 91 5.33 1 61 0 1
#> 105 19.75 1 60 0 0
#> 133 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 127.1 3.53 1 62 0 1
#> 89 11.44 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 39 15.59 1 37 0 1
#> 149.1 8.37 1 33 1 0
#> 130 16.47 1 53 0 1
#> 52.1 10.42 1 52 0 1
#> 58 19.34 1 39 0 0
#> 189 10.51 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 167 15.55 1 56 1 0
#> 57 14.46 1 45 0 1
#> 16 8.71 1 71 0 1
#> 192 16.44 1 31 1 0
#> 32 20.90 1 37 1 0
#> 90 20.94 1 50 0 1
#> 177 12.53 1 75 0 0
#> 57.1 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 159 10.55 1 50 0 1
#> 150.1 20.33 1 48 0 0
#> 90.1 20.94 1 50 0 1
#> 60 13.15 1 38 1 0
#> 97 19.14 1 65 0 1
#> 192.1 16.44 1 31 1 0
#> 10 10.53 1 34 0 0
#> 68 20.62 1 44 0 0
#> 90.2 20.94 1 50 0 1
#> 5 16.43 1 51 0 1
#> 134 17.81 1 47 1 0
#> 136 21.83 1 43 0 1
#> 99 21.19 1 38 0 1
#> 127.2 3.53 1 62 0 1
#> 25.1 6.32 1 34 1 0
#> 68.1 20.62 1 44 0 0
#> 111 17.45 1 47 0 1
#> 76.1 19.22 1 54 0 1
#> 192.2 16.44 1 31 1 0
#> 157 15.10 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 113 22.86 1 34 0 0
#> 127.3 3.53 1 62 0 1
#> 167.1 15.55 1 56 1 0
#> 130.1 16.47 1 53 0 1
#> 183 9.24 1 67 1 0
#> 30 17.43 1 78 0 0
#> 129 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 197 21.60 1 69 1 0
#> 10.1 10.53 1 34 0 0
#> 164.1 23.60 1 76 0 1
#> 13.1 14.34 1 54 0 1
#> 111.1 17.45 1 47 0 1
#> 117 17.46 1 26 0 1
#> 26 15.77 1 49 0 1
#> 6.1 15.64 1 39 0 0
#> 39.1 15.59 1 37 0 1
#> 125 15.65 1 67 1 0
#> 50.1 10.02 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 181.1 16.46 1 45 0 1
#> 140 12.68 1 59 1 0
#> 14 12.89 1 21 0 0
#> 55.1 19.34 1 69 0 1
#> 195 11.76 1 NA 1 0
#> 164.2 23.60 1 76 0 1
#> 58.1 19.34 1 39 0 0
#> 108 18.29 1 39 0 1
#> 10.2 10.53 1 34 0 0
#> 100 16.07 1 60 0 0
#> 181.2 16.46 1 45 0 1
#> 192.3 16.44 1 31 1 0
#> 39.2 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 123 13.00 1 44 1 0
#> 68.2 20.62 1 44 0 0
#> 30.1 17.43 1 78 0 0
#> 114 13.68 1 NA 0 0
#> 14.1 12.89 1 21 0 0
#> 42.1 12.43 1 49 0 1
#> 78 23.88 1 43 0 0
#> 76.2 19.22 1 54 0 1
#> 58.2 19.34 1 39 0 0
#> 164.3 23.60 1 76 0 1
#> 56.1 12.21 1 60 0 0
#> 18 15.21 1 49 1 0
#> 159.1 10.55 1 50 0 1
#> 85.1 16.44 1 36 0 0
#> 117.1 17.46 1 26 0 1
#> 61.1 10.12 1 36 0 1
#> 146 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 116 24.00 0 58 0 1
#> 191 24.00 0 60 0 1
#> 73 24.00 0 NA 0 1
#> 173 24.00 0 19 0 1
#> 191.1 24.00 0 60 0 1
#> 103 24.00 0 56 1 0
#> 94 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 172 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 132 24.00 0 55 0 0
#> 3 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 119.1 24.00 0 17 0 0
#> 200 24.00 0 64 0 0
#> 67 24.00 0 25 0 0
#> 62 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 44 24.00 0 56 0 0
#> 47 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 82.1 24.00 0 34 0 0
#> 151.1 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 33 24.00 0 53 0 0
#> 83.1 24.00 0 6 0 0
#> 84 24.00 0 39 0 1
#> 65.1 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 116.1 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 7 24.00 0 37 1 0
#> 67.1 24.00 0 25 0 0
#> 141 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 53.1 24.00 0 32 0 1
#> 147 24.00 0 76 1 0
#> 12.1 24.00 0 63 0 0
#> 161.1 24.00 0 45 0 0
#> 173.2 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 137 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 95.1 24.00 0 68 0 1
#> 191.2 24.00 0 60 0 1
#> 137.1 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 119.2 24.00 0 17 0 0
#> 191.3 24.00 0 60 0 1
#> 185 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 198 24.00 0 66 0 1
#> 2 24.00 0 9 0 0
#> 87 24.00 0 27 0 0
#> 141.1 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 193 24.00 0 45 0 1
#> 151.2 24.00 0 42 0 0
#> 74.1 24.00 0 43 0 1
#> 137.2 24.00 0 45 1 0
#> 191.4 24.00 0 60 0 1
#> 3.1 24.00 0 31 1 0
#> 95.2 24.00 0 68 0 1
#> 27.1 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 135.1 24.00 0 58 1 0
#> 3.2 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.582 NA NA NA
#> 2 age, Cure model 0.00982 NA NA NA
#> 3 grade_ii, Cure model 0.000681 NA NA NA
#> 4 grade_iii, Cure model 0.784 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0204 NA NA NA
#> 2 grade_ii, Survival model 0.543 NA NA NA
#> 3 grade_iii, Survival model 0.320 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5820936 0.0098211 0.0006808 0.7836288
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 255.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5820936321 0.0098211072 0.0006808059 0.7836287588
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02035701 0.54281160 0.31950918
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 5.919763e-01 2.320266e-04 9.293391e-01 8.441444e-01 4.042398e-02
#> [6] 3.132671e-01 5.066859e-05 8.779697e-01 9.653502e-02 2.605021e-02
#> [11] 8.385090e-02 6.209210e-01 1.804737e-01 4.813734e-01 7.284866e-01
#> [16] 7.937956e-01 9.119770e-01 3.267565e-02 4.171426e-01 4.551466e-01
#> [21] 9.293391e-01 6.191831e-02 3.353944e-01 8.441444e-01 1.631520e-01
#> [26] 7.284866e-01 4.042398e-02 5.636386e-01 3.691909e-01 4.297135e-01
#> [31] 8.271421e-01 2.075338e-01 1.552422e-02 9.445560e-03 5.776715e-01
#> [36] 4.297135e-01 1.102131e-01 6.508495e-01 2.605021e-02 9.445560e-03
#> [41] 4.948565e-01 7.785063e-02 2.075338e-01 6.814862e-01 1.796499e-02
#> [46] 9.445560e-03 2.611803e-01 1.032973e-01 4.406916e-03 7.580341e-03
#> [51] 9.293391e-01 8.779697e-01 1.796499e-02 1.317010e-01 6.191831e-02
#> [56] 2.075338e-01 4.048266e-01 2.711922e-01 3.127040e-03 9.293391e-01
#> [61] 3.691909e-01 1.631520e-01 8.103728e-01 1.467572e-01 2.066530e-03
#> [66] 7.609038e-01 5.869963e-03 6.814862e-01 2.320266e-04 4.551466e-01
#> [71] 1.317010e-01 1.174153e-01 2.918027e-01 3.132671e-01 3.353944e-01
#> [76] 3.024283e-01 3.646198e-02 1.804737e-01 5.495548e-01 5.220833e-01
#> [81] 4.042398e-02 2.320266e-04 4.042398e-02 9.010861e-02 6.814862e-01
#> [86] 2.813644e-01 1.804737e-01 2.075338e-01 3.353944e-01 2.075338e-01
#> [91] 5.084157e-01 1.796499e-02 1.467572e-01 5.220833e-01 5.919763e-01
#> [96] 4.597846e-06 6.191831e-02 4.042398e-02 2.320266e-04 6.209210e-01
#> [101] 3.927371e-01 6.508495e-01 2.075338e-01 1.174153e-01 7.609038e-01
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 42 164 127 149 55 6 168 25 51 150 179 56 181
#> 12.43 23.60 3.53 8.37 19.34 15.64 23.72 6.32 18.23 20.33 18.63 12.21 16.46
#> 81 52 101 91 105 133 13 127.1 76 39 149.1 130 52.1
#> 14.06 10.42 9.97 5.33 19.75 14.65 14.34 3.53 19.22 15.59 8.37 16.47 10.42
#> 58 154 167 57 16 192 32 90 177 57.1 110 159 150.1
#> 19.34 12.63 15.55 14.46 8.71 16.44 20.90 20.94 12.53 14.46 17.56 10.55 20.33
#> 90.1 60 97 192.1 10 68 90.2 5 134 136 99 127.2 25.1
#> 20.94 13.15 19.14 16.44 10.53 20.62 20.94 16.43 17.81 21.83 21.19 3.53 6.32
#> 68.1 111 76.1 192.2 157 79 113 127.3 167.1 130.1 183 30 129
#> 20.62 17.45 19.22 16.44 15.10 16.23 22.86 3.53 15.55 16.47 9.24 17.43 23.41
#> 61 197 10.1 164.1 13.1 111.1 117 26 6.1 39.1 125 170 181.1
#> 10.12 21.60 10.53 23.60 14.34 17.45 17.46 15.77 15.64 15.59 15.65 19.54 16.46
#> 140 14 55.1 164.2 58.1 108 10.2 100 181.2 192.3 39.2 85 123
#> 12.68 12.89 19.34 23.60 19.34 18.29 10.53 16.07 16.46 16.44 15.59 16.44 13.00
#> 68.2 30.1 14.1 42.1 78 76.2 58.2 164.3 56.1 18 159.1 85.1 117.1
#> 20.62 17.43 12.89 12.43 23.88 19.22 19.34 23.60 12.21 15.21 10.55 16.44 17.46
#> 61.1 146 162 48 151 116 191 173 191.1 103 94 35 119
#> 10.12 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 83 65 135 132 3 35.1 82 119.1 200 67 62 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 44 47 120 53 82.1 151.1 161 33 83.1 84 65.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 116.1 12 7 67.1 141 131.1 74 27 104 182 53.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 161.1 173.2 142 22 17 144 137 109 95.1 191.2 137.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 119.2 191.3 185 102 198 2 87 141.1 48.1 126 193 151.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 137.2 191.4 3.1 95.2 27.1 64 135.1 3.2 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[35]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004122667 0.451026039 0.620324374
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.535023841 0.004960698 0.541280557
#> grade_iii, Cure model
#> 1.145136537
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 123 13.00 1 44 1 0
#> 96 14.54 1 33 0 1
#> 140 12.68 1 59 1 0
#> 52 10.42 1 52 0 1
#> 5 16.43 1 51 0 1
#> 168 23.72 1 70 0 0
#> 166 19.98 1 48 0 0
#> 197 21.60 1 69 1 0
#> 158 20.14 1 74 1 0
#> 69 23.23 1 25 0 1
#> 41 18.02 1 40 1 0
#> 114 13.68 1 NA 0 0
#> 129 23.41 1 53 1 0
#> 113 22.86 1 34 0 0
#> 188 16.16 1 46 0 1
#> 100 16.07 1 60 0 0
#> 85 16.44 1 36 0 0
#> 145 10.07 1 65 1 0
#> 55 19.34 1 69 0 1
#> 139 21.49 1 63 1 0
#> 106 16.67 1 49 1 0
#> 128 20.35 1 35 0 1
#> 110 17.56 1 65 0 1
#> 139.1 21.49 1 63 1 0
#> 41.1 18.02 1 40 1 0
#> 61 10.12 1 36 0 1
#> 37 12.52 1 57 1 0
#> 169 22.41 1 46 0 0
#> 39 15.59 1 37 0 1
#> 8 18.43 1 32 0 0
#> 42 12.43 1 49 0 1
#> 91 5.33 1 61 0 1
#> 18 15.21 1 49 1 0
#> 57 14.46 1 45 0 1
#> 92 22.92 1 47 0 1
#> 169.1 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 13 14.34 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 139.2 21.49 1 63 1 0
#> 63 22.77 1 31 1 0
#> 57.1 14.46 1 45 0 1
#> 52.1 10.42 1 52 0 1
#> 61.1 10.12 1 36 0 1
#> 111 17.45 1 47 0 1
#> 190 20.81 1 42 1 0
#> 139.3 21.49 1 63 1 0
#> 113.1 22.86 1 34 0 0
#> 91.1 5.33 1 61 0 1
#> 114.1 13.68 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 70 7.38 1 30 1 0
#> 78 23.88 1 43 0 0
#> 101 9.97 1 10 0 1
#> 125.1 15.65 1 67 1 0
#> 150 20.33 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 159 10.55 1 50 0 1
#> 79 16.23 1 54 1 0
#> 16.1 8.71 1 71 0 1
#> 136 21.83 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 192 16.44 1 31 1 0
#> 184 17.77 1 38 0 0
#> 88 18.37 1 47 0 0
#> 18.1 15.21 1 49 1 0
#> 92.1 22.92 1 47 0 1
#> 133 14.65 1 57 0 0
#> 60 13.15 1 38 1 0
#> 51 18.23 1 83 0 1
#> 155 13.08 1 26 0 0
#> 61.2 10.12 1 36 0 1
#> 69.1 23.23 1 25 0 1
#> 25 6.32 1 34 1 0
#> 177 12.53 1 75 0 0
#> 68 20.62 1 44 0 0
#> 60.1 13.15 1 38 1 0
#> 107 11.18 1 54 1 0
#> 110.1 17.56 1 65 0 1
#> 139.4 21.49 1 63 1 0
#> 49 12.19 1 48 1 0
#> 139.5 21.49 1 63 1 0
#> 68.1 20.62 1 44 0 0
#> 181 16.46 1 45 0 1
#> 29 15.45 1 68 1 0
#> 123.1 13.00 1 44 1 0
#> 43 12.10 1 61 0 1
#> 29.1 15.45 1 68 1 0
#> 18.2 15.21 1 49 1 0
#> 190.1 20.81 1 42 1 0
#> 145.1 10.07 1 65 1 0
#> 10.1 10.53 1 34 0 0
#> 24 23.89 1 38 0 0
#> 181.1 16.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 190.2 20.81 1 42 1 0
#> 90 20.94 1 50 0 1
#> 85.1 16.44 1 36 0 0
#> 91.2 5.33 1 61 0 1
#> 45 17.42 1 54 0 1
#> 108 18.29 1 39 0 1
#> 23 16.92 1 61 0 0
#> 56 12.21 1 60 0 0
#> 188.1 16.16 1 46 0 1
#> 45.1 17.42 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 18.3 15.21 1 49 1 0
#> 15 22.68 1 48 0 0
#> 192.1 16.44 1 31 1 0
#> 109 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 174 24.00 0 49 1 0
#> 144 24.00 0 28 0 1
#> 46 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 162 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 174.1 24.00 0 49 1 0
#> 20 24.00 0 46 1 0
#> 148 24.00 0 61 1 0
#> 104.1 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 84 24.00 0 39 0 1
#> 34 24.00 0 36 0 0
#> 143 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 75 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 33 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 34.1 24.00 0 36 0 0
#> 182 24.00 0 35 0 0
#> 178 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 186 24.00 0 45 1 0
#> 160 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 71 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 2.1 24.00 0 9 0 0
#> 104.2 24.00 0 50 1 0
#> 112.1 24.00 0 61 0 0
#> 176 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 3 24.00 0 31 1 0
#> 34.2 24.00 0 36 0 0
#> 82.1 24.00 0 34 0 0
#> 87 24.00 0 27 0 0
#> 22.1 24.00 0 52 1 0
#> 116 24.00 0 58 0 1
#> 33.1 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 71.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 198 24.00 0 66 0 1
#> 28 24.00 0 67 1 0
#> 121 24.00 0 57 1 0
#> 193 24.00 0 45 0 1
#> 109.1 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 174.2 24.00 0 49 1 0
#> 48 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 73.1 24.00 0 NA 0 1
#> 19 24.00 0 57 0 1
#> 11 24.00 0 42 0 1
#> 20.1 24.00 0 46 1 0
#> 62.1 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 143.1 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 121.1 24.00 0 57 1 0
#> 34.3 24.00 0 36 0 0
#> 35 24.00 0 51 0 0
#> 119.1 24.00 0 17 0 0
#> 28.1 24.00 0 67 1 0
#> 191 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 193.1 24.00 0 45 0 1
#> 27 24.00 0 63 1 0
#> 20.2 24.00 0 46 1 0
#> 144.1 24.00 0 28 0 1
#> 82.2 24.00 0 34 0 0
#> 71.2 24.00 0 51 0 0
#> 19.1 24.00 0 57 0 1
#> 7.1 24.00 0 37 1 0
#> 19.2 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.535 NA NA NA
#> 2 age, Cure model 0.00496 NA NA NA
#> 3 grade_ii, Cure model 0.541 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00412 NA NA NA
#> 2 grade_ii, Survival model 0.451 NA NA NA
#> 3 grade_iii, Survival model 0.620 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.535024 0.004961 0.541281 1.145137
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 253.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.535023841 0.004960698 0.541280557 1.145136537
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004122667 0.451026039 0.620324374
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.84435738 0.80298049 0.86161901 0.92295443 0.70690027 0.11034192
#> [7] 0.51921704 0.34852095 0.51005005 0.17259366 0.58874848 0.14460316
#> [13] 0.24360123 0.72059665 0.73385389 0.67943939 0.94937375 0.52834875
#> [19] 0.36201920 0.65799119 0.49129763 0.61283030 0.36201920 0.58874848
#> [25] 0.93366536 0.87305753 0.30538056 0.75347228 0.53725400 0.87873336
#> [31] 0.98522855 0.77254163 0.80906231 0.21178246 0.30538056 0.74049582
#> [37] 0.82095954 0.53725400 0.43351318 0.36201920 0.27481314 0.80906231
#> [43] 0.92295443 0.93366536 0.62825065 0.44379929 0.36201920 0.24360123
#> [49] 0.98522855 0.96493230 0.97509826 0.07227607 0.95975426 0.74049582
#> [55] 0.50069305 0.91207890 0.90661500 0.71378004 0.96493230 0.33442988
#> [61] 0.67943939 0.60477928 0.55483544 0.77254163 0.21178246 0.79684613
#> [67] 0.82687297 0.57233727 0.83851874 0.93366536 0.17259366 0.98017395
#> [73] 0.86734510 0.47227279 0.82687297 0.90110845 0.61283030 0.36201920
#> [79] 0.88998218 0.36201920 0.47227279 0.66529482 0.75992363 0.84435738
#> [85] 0.89556935 0.75992363 0.77254163 0.44379929 0.94937375 0.91207890
#> [91] 0.03073799 0.66529482 0.85585452 0.44379929 0.42302080 0.67943939
#> [97] 0.98522855 0.63589013 0.56366677 0.65061209 0.88436279 0.72059665
#> [103] 0.63589013 0.57233727 0.77254163 0.29018481 0.67943939 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 123 96 140 52 5 168 166 197 158 69 41 129 113
#> 13.00 14.54 12.68 10.42 16.43 23.72 19.98 21.60 20.14 23.23 18.02 23.41 22.86
#> 188 100 85 145 55 139 106 128 110 139.1 41.1 61 37
#> 16.16 16.07 16.44 10.07 19.34 21.49 16.67 20.35 17.56 21.49 18.02 10.12 12.52
#> 169 39 8 42 91 18 57 92 169.1 125 13 8.1 32
#> 22.41 15.59 18.43 12.43 5.33 15.21 14.46 22.92 22.41 15.65 14.34 18.43 20.90
#> 139.2 63 57.1 52.1 61.1 111 190 139.3 113.1 91.1 16 70 78
#> 21.49 22.77 14.46 10.42 10.12 17.45 20.81 21.49 22.86 5.33 8.71 7.38 23.88
#> 101 125.1 150 10 159 79 16.1 136 192 184 88 18.1 92.1
#> 9.97 15.65 20.33 10.53 10.55 16.23 8.71 21.83 16.44 17.77 18.37 15.21 22.92
#> 133 60 51 155 61.2 69.1 25 177 68 60.1 107 110.1 139.4
#> 14.65 13.15 18.23 13.08 10.12 23.23 6.32 12.53 20.62 13.15 11.18 17.56 21.49
#> 49 139.5 68.1 181 29 123.1 43 29.1 18.2 190.1 145.1 10.1 24
#> 12.19 21.49 20.62 16.46 15.45 13.00 12.10 15.45 15.21 20.81 10.07 10.53 23.89
#> 181.1 14 190.2 90 85.1 91.2 45 108 23 56 188.1 45.1 51.1
#> 16.46 12.89 20.81 20.94 16.44 5.33 17.42 18.29 16.92 12.21 16.16 17.42 18.23
#> 18.3 15 192.1 109 120 104 165 200 174 144 46 82 162
#> 15.21 22.68 16.44 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 156 122 174.1 20 148 104.1 137 112 84 34 143 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 33 103 34.1 182 178 2 186 160 9 196 71 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 104.2 112.1 176 119 3 34.2 82.1 87 22.1 116 33.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 120.1 198 28 121 193 109.1 7 174.2 48 94 19 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 62.1 54 143.1 172 126 147 121.1 34.3 35 119.1 28.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 193.1 27 20.2 144.1 82.2 71.2 19.1 7.1 19.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[36]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006652258 0.706496322 0.837317092
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86057278 0.02524298 -0.51145992
#> grade_iii, Cure model
#> 0.22738415
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 145 10.07 1 65 1 0
#> 79 16.23 1 54 1 0
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 42 12.43 1 49 0 1
#> 93 10.33 1 52 0 1
#> 184 17.77 1 38 0 0
#> 153 21.33 1 55 1 0
#> 197 21.60 1 69 1 0
#> 129 23.41 1 53 1 0
#> 52 10.42 1 52 0 1
#> 153.1 21.33 1 55 1 0
#> 24 23.89 1 38 0 0
#> 51 18.23 1 83 0 1
#> 85 16.44 1 36 0 0
#> 56.1 12.21 1 60 0 0
#> 169 22.41 1 46 0 0
#> 158 20.14 1 74 1 0
#> 90 20.94 1 50 0 1
#> 55 19.34 1 69 0 1
#> 36 21.19 1 48 0 1
#> 101 9.97 1 10 0 1
#> 125 15.65 1 67 1 0
#> 199 19.81 1 NA 0 1
#> 4 17.64 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 133 14.65 1 57 0 0
#> 24.1 23.89 1 38 0 0
#> 113 22.86 1 34 0 0
#> 134 17.81 1 47 1 0
#> 32 20.90 1 37 1 0
#> 61 10.12 1 36 0 1
#> 24.2 23.89 1 38 0 0
#> 183 9.24 1 67 1 0
#> 117 17.46 1 26 0 1
#> 157 15.10 1 47 0 0
#> 16 8.71 1 71 0 1
#> 107 11.18 1 54 1 0
#> 187 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 177 12.53 1 75 0 0
#> 194 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 70 7.38 1 30 1 0
#> 88 18.37 1 47 0 0
#> 78 23.88 1 43 0 0
#> 149 8.37 1 33 1 0
#> 45 17.42 1 54 0 1
#> 79.1 16.23 1 54 1 0
#> 68 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 8 18.43 1 32 0 0
#> 168 23.72 1 70 0 0
#> 125.1 15.65 1 67 1 0
#> 52.1 10.42 1 52 0 1
#> 24.3 23.89 1 38 0 0
#> 90.1 20.94 1 50 0 1
#> 166 19.98 1 48 0 0
#> 175 21.91 1 43 0 0
#> 23 16.92 1 61 0 0
#> 166.1 19.98 1 48 0 0
#> 43 12.10 1 61 0 1
#> 52.2 10.42 1 52 0 1
#> 93.1 10.33 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 26 15.77 1 49 0 1
#> 124.1 9.73 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 51.1 18.23 1 83 0 1
#> 63 22.77 1 31 1 0
#> 10 10.53 1 34 0 0
#> 15 22.68 1 48 0 0
#> 167 15.55 1 56 1 0
#> 24.4 23.89 1 38 0 0
#> 88.1 18.37 1 47 0 0
#> 78.1 23.88 1 43 0 0
#> 76 19.22 1 54 0 1
#> 10.1 10.53 1 34 0 0
#> 190 20.81 1 42 1 0
#> 36.1 21.19 1 48 0 1
#> 108 18.29 1 39 0 1
#> 55.1 19.34 1 69 0 1
#> 15.1 22.68 1 48 0 0
#> 66 22.13 1 53 0 0
#> 39 15.59 1 37 0 1
#> 88.2 18.37 1 47 0 0
#> 43.1 12.10 1 61 0 1
#> 184.1 17.77 1 38 0 0
#> 171 16.57 1 41 0 1
#> 36.2 21.19 1 48 0 1
#> 51.2 18.23 1 83 0 1
#> 123 13.00 1 44 1 0
#> 153.2 21.33 1 55 1 0
#> 155 13.08 1 26 0 0
#> 157.1 15.10 1 47 0 0
#> 58 19.34 1 39 0 0
#> 136 21.83 1 43 0 1
#> 13.1 14.34 1 54 0 1
#> 6 15.64 1 39 0 0
#> 100 16.07 1 60 0 0
#> 26.1 15.77 1 49 0 1
#> 113.1 22.86 1 34 0 0
#> 10.2 10.53 1 34 0 0
#> 56.2 12.21 1 60 0 0
#> 100.1 16.07 1 60 0 0
#> 123.1 13.00 1 44 1 0
#> 194.1 22.40 1 38 0 1
#> 190.1 20.81 1 42 1 0
#> 168.1 23.72 1 70 0 0
#> 183.1 9.24 1 67 1 0
#> 148 24.00 0 61 1 0
#> 102 24.00 0 49 0 0
#> 17 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 132 24.00 0 55 0 0
#> 176 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#> 172 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 54 24.00 0 53 1 0
#> 176.1 24.00 0 43 0 1
#> 7 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 82.1 24.00 0 34 0 0
#> 3 24.00 0 31 1 0
#> 54.1 24.00 0 53 1 0
#> 1 24.00 0 23 1 0
#> 83 24.00 0 6 0 0
#> 65 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 132.1 24.00 0 55 0 0
#> 7.1 24.00 0 37 1 0
#> 22.1 24.00 0 52 1 0
#> 116 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 65.1 24.00 0 57 1 0
#> 144.1 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 53.1 24.00 0 32 0 1
#> 174 24.00 0 49 1 0
#> 80 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 11.1 24.00 0 42 0 1
#> 126 24.00 0 48 0 0
#> 2.1 24.00 0 9 0 0
#> 182 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 173 24.00 0 19 0 1
#> 147.1 24.00 0 76 1 0
#> 65.2 24.00 0 57 1 0
#> 143 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 38 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 21 24.00 0 47 0 0
#> 144.2 24.00 0 28 0 1
#> 121.1 24.00 0 57 1 0
#> 115 24.00 0 NA 1 0
#> 198 24.00 0 66 0 1
#> 27.1 24.00 0 63 1 0
#> 22.2 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#> 94 24.00 0 51 0 1
#> 115.1 24.00 0 NA 1 0
#> 112 24.00 0 61 0 0
#> 121.2 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 65.3 24.00 0 57 1 0
#> 102.1 24.00 0 49 0 0
#> 196.1 24.00 0 19 0 0
#> 163 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 163.1 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 143.1 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 112.1 24.00 0 61 0 0
#> 38.1 24.00 0 31 1 0
#> 196.2 24.00 0 19 0 0
#> 137.1 24.00 0 45 1 0
#> 94.1 24.00 0 51 0 1
#> 11.2 24.00 0 42 0 1
#> 143.2 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 116.1 24.00 0 58 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.861 NA NA NA
#> 2 age, Cure model 0.0252 NA NA NA
#> 3 grade_ii, Cure model -0.511 NA NA NA
#> 4 grade_iii, Cure model 0.227 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00665 NA NA NA
#> 2 grade_ii, Survival model 0.706 NA NA NA
#> 3 grade_iii, Survival model 0.837 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86057 0.02524 -0.51146 0.22738
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 255 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86057278 0.02524298 -0.51145992 0.22738415
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006652258 0.706496322 0.837317092
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.95976006 0.77515642 0.66749044 0.88848121 0.88374448 0.94706080
#> [7] 0.73352350 0.50832890 0.48398127 0.28978968 0.93410088 0.50832890
#> [13] 0.09091898 0.70881697 0.76936186 0.88848121 0.39744160 0.61596075
#> [19] 0.56639075 0.63905145 0.53905694 0.96393631 0.80835025 0.83445928
#> [25] 0.84962129 0.09091898 0.30953598 0.72737686 0.58352816 0.95554486
#> [31] 0.09091898 0.97220725 0.74570679 0.83953841 0.98028402 0.91622193
#> [37] 0.96808615 0.49646562 0.87895122 0.41415305 0.90250633 0.98826348
#> [43] 0.68149669 0.19767078 0.98428608 0.75173713 0.77515642 0.60794971
#> [49] 0.85466394 0.67450219 0.24625677 0.80835025 0.93410088 0.09091898
#> [55] 0.56639075 0.62373755 0.45668471 0.75765783 0.62373755 0.90716242
#> [61] 0.93410088 0.94706080 0.98826348 0.79753349 0.99610935 0.70881697
#> [67] 0.34661372 0.92072050 0.36423251 0.82932364 0.09091898 0.68149669
#> [73] 0.19767078 0.66045487 0.92072050 0.59196203 0.53905694 0.70203589
#> [79] 0.63905145 0.36423251 0.44248152 0.82412549 0.68149669 0.90716242
#> [85] 0.73352350 0.76355547 0.53905694 0.70881697 0.86935708 0.50832890
#> [91] 0.86445358 0.83953841 0.63905145 0.47074315 0.85466394 0.81886245
#> [97] 0.78638399 0.79753349 0.30953598 0.92072050 0.88848121 0.78638399
#> [103] 0.86935708 0.41415305 0.59196203 0.24625677 0.97220725 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 145 79 179 56 42 93 184 153 197 129 52 153.1 24
#> 10.07 16.23 18.63 12.21 12.43 10.33 17.77 21.33 21.60 23.41 10.42 21.33 23.89
#> 51 85 56.1 169 158 90 55 36 101 125 18 133 24.1
#> 18.23 16.44 12.21 22.41 20.14 20.94 19.34 21.19 9.97 15.65 15.21 14.65 23.89
#> 113 134 32 61 24.2 183 117 157 16 107 187 139 177
#> 22.86 17.81 20.90 10.12 23.89 9.24 17.46 15.10 8.71 11.18 9.92 21.49 12.53
#> 194 49 70 88 78 149 45 79.1 68 13 8 168 125.1
#> 22.40 12.19 7.38 18.37 23.88 8.37 17.42 16.23 20.62 14.34 18.43 23.72 15.65
#> 52.1 24.3 90.1 166 175 23 166.1 43 52.2 93.1 70.1 26 77
#> 10.42 23.89 20.94 19.98 21.91 16.92 19.98 12.10 10.42 10.33 7.38 15.77 7.27
#> 51.1 63 10 15 167 24.4 88.1 78.1 76 10.1 190 36.1 108
#> 18.23 22.77 10.53 22.68 15.55 23.89 18.37 23.88 19.22 10.53 20.81 21.19 18.29
#> 55.1 15.1 66 39 88.2 43.1 184.1 171 36.2 51.2 123 153.2 155
#> 19.34 22.68 22.13 15.59 18.37 12.10 17.77 16.57 21.19 18.23 13.00 21.33 13.08
#> 157.1 58 136 13.1 6 100 26.1 113.1 10.2 56.2 100.1 123.1 194.1
#> 15.10 19.34 21.83 14.34 15.64 16.07 15.77 22.86 10.53 12.21 16.07 13.00 22.40
#> 190.1 168.1 183.1 148 102 17 186 74 9 22 11 132 176
#> 20.81 23.72 9.24 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 82 172 162 151 54 176.1 7 144 53 82.1 3 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 83 65 103 132.1 7.1 22.1 116 65.1 144.1 147 53.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 137 11.1 126 2.1 182 121 27 173 147.1 65.2 143 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 118 165 21 144.2 121.1 198 27.1 22.2 200 94 112 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 65.3 102.1 196.1 163 152 46 163.1 131 143.1 185 71 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 112.1 38.1 196.2 137.1 94.1 11.2 143.2 151.1 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[37]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01126948 0.46694548 0.47525685
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.164265777 0.002994013 0.157551104
#> grade_iii, Cure model
#> 0.671427645
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 26 15.77 1 49 0 1
#> 68 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 129 23.41 1 53 1 0
#> 113 22.86 1 34 0 0
#> 49 12.19 1 48 1 0
#> 184 17.77 1 38 0 0
#> 6 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 129.1 23.41 1 53 1 0
#> 199 19.81 1 NA 0 1
#> 99 21.19 1 38 0 1
#> 60 13.15 1 38 1 0
#> 96 14.54 1 33 0 1
#> 183 9.24 1 67 1 0
#> 13.1 14.34 1 54 0 1
#> 134 17.81 1 47 1 0
#> 107 11.18 1 54 1 0
#> 106 16.67 1 49 1 0
#> 166 19.98 1 48 0 0
#> 40 18.00 1 28 1 0
#> 124 9.73 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 78 23.88 1 43 0 0
#> 101 9.97 1 10 0 1
#> 117 17.46 1 26 0 1
#> 128 20.35 1 35 0 1
#> 37 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 25 6.32 1 34 1 0
#> 86 23.81 1 58 0 1
#> 140 12.68 1 59 1 0
#> 63 22.77 1 31 1 0
#> 96.1 14.54 1 33 0 1
#> 125.1 15.65 1 67 1 0
#> 58 19.34 1 39 0 0
#> 36 21.19 1 48 0 1
#> 128.1 20.35 1 35 0 1
#> 63.1 22.77 1 31 1 0
#> 14 12.89 1 21 0 0
#> 79.1 16.23 1 54 1 0
#> 170 19.54 1 43 0 1
#> 6.1 15.64 1 39 0 0
#> 167 15.55 1 56 1 0
#> 58.1 19.34 1 39 0 0
#> 158 20.14 1 74 1 0
#> 24 23.89 1 38 0 0
#> 6.2 15.64 1 39 0 0
#> 188 16.16 1 46 0 1
#> 100 16.07 1 60 0 0
#> 90 20.94 1 50 0 1
#> 58.2 19.34 1 39 0 0
#> 8 18.43 1 32 0 0
#> 40.1 18.00 1 28 1 0
#> 42 12.43 1 49 0 1
#> 159 10.55 1 50 0 1
#> 128.2 20.35 1 35 0 1
#> 136 21.83 1 43 0 1
#> 153 21.33 1 55 1 0
#> 139.1 21.49 1 63 1 0
#> 24.1 23.89 1 38 0 0
#> 190 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 136.1 21.83 1 43 0 1
#> 58.3 19.34 1 39 0 0
#> 139.2 21.49 1 63 1 0
#> 57 14.46 1 45 0 1
#> 166.1 19.98 1 48 0 0
#> 110 17.56 1 65 0 1
#> 97 19.14 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 32 20.90 1 37 1 0
#> 37.1 12.52 1 57 1 0
#> 85 16.44 1 36 0 0
#> 111 17.45 1 47 0 1
#> 149 8.37 1 33 1 0
#> 25.1 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 25.2 6.32 1 34 1 0
#> 139.3 21.49 1 63 1 0
#> 45 17.42 1 54 0 1
#> 150 20.33 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 177 12.53 1 75 0 0
#> 153.1 21.33 1 55 1 0
#> 59 10.16 1 NA 1 0
#> 58.4 19.34 1 39 0 0
#> 197 21.60 1 69 1 0
#> 166.2 19.98 1 48 0 0
#> 86.1 23.81 1 58 0 1
#> 123 13.00 1 44 1 0
#> 58.5 19.34 1 39 0 0
#> 59.1 10.16 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 168 23.72 1 70 0 0
#> 70 7.38 1 30 1 0
#> 8.1 18.43 1 32 0 0
#> 159.1 10.55 1 50 0 1
#> 56 12.21 1 60 0 0
#> 96.2 14.54 1 33 0 1
#> 150.1 20.33 1 48 0 0
#> 97.1 19.14 1 65 0 1
#> 36.1 21.19 1 48 0 1
#> 61 10.12 1 36 0 1
#> 42.1 12.43 1 49 0 1
#> 18 15.21 1 49 1 0
#> 100.1 16.07 1 60 0 0
#> 115 24.00 0 NA 1 0
#> 84 24.00 0 39 0 1
#> 191 24.00 0 60 0 1
#> 174 24.00 0 49 1 0
#> 185 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 84.1 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 17 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 148 24.00 0 61 1 0
#> 80 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 98 24.00 0 34 1 0
#> 115.1 24.00 0 NA 1 0
#> 191.1 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 131 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 12 24.00 0 63 0 0
#> 65 24.00 0 57 1 0
#> 46 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 67.1 24.00 0 25 0 0
#> 46.1 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 48 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 3 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 115.2 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 186 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 80.1 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 87 24.00 0 27 0 0
#> 20 24.00 0 46 1 0
#> 3.1 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 147 24.00 0 76 1 0
#> 137 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 120 24.00 0 68 0 1
#> 44.2 24.00 0 56 0 0
#> 109 24.00 0 48 0 0
#> 148.1 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 22.1 24.00 0 52 1 0
#> 53.1 24.00 0 32 0 1
#> 178.1 24.00 0 52 1 0
#> 17.1 24.00 0 38 0 1
#> 148.2 24.00 0 61 1 0
#> 198.1 24.00 0 66 0 1
#> 2 24.00 0 9 0 0
#> 47 24.00 0 38 0 1
#> 31.1 24.00 0 36 0 1
#> 28.1 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 104 24.00 0 50 1 0
#> 80.2 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 132.1 24.00 0 55 0 0
#> 53.2 24.00 0 32 0 1
#> 131.1 24.00 0 66 0 0
#> 22.2 24.00 0 52 1 0
#> 17.2 24.00 0 38 0 1
#> 148.3 24.00 0 61 1 0
#> 132.2 24.00 0 55 0 0
#> 31.2 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 163 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 44.3 24.00 0 56 0 0
#> 165.1 24.00 0 47 0 0
#> 27 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 121 24.00 0 57 1 0
#> 83.1 24.00 0 6 0 0
#> 146 24.00 0 63 1 0
#> 103 24.00 0 56 1 0
#> 186.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.164 NA NA NA
#> 2 age, Cure model 0.00299 NA NA NA
#> 3 grade_ii, Cure model 0.158 NA NA NA
#> 4 grade_iii, Cure model 0.671 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0113 NA NA NA
#> 2 grade_ii, Survival model 0.467 NA NA NA
#> 3 grade_iii, Survival model 0.475 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.164266 0.002994 0.157551 0.671428
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 260 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.164265777 0.002994013 0.157551104 0.671427645
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01126948 0.46694548 0.47525685
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.695991247 0.559926340 0.194178223 0.890473532 0.033091705 0.046710206
#> [7] 0.835556814 0.419515444 0.590933793 0.099064346 0.033091705 0.145289859
#> [13] 0.727766190 0.654136893 0.934528982 0.695991247 0.409676846 0.857521966
#> [19] 0.469237800 0.252551342 0.390263950 0.570262628 0.717088462 0.846525769
#> [25] 0.499345374 0.008797197 0.912566017 0.439406986 0.202677666 0.781378396
#> [31] 0.068523767 0.967522235 0.014812434 0.759821808 0.054499093 0.654136893
#> [37] 0.570262628 0.288016657 0.145289859 0.202677666 0.054499093 0.749113694
#> [43] 0.499345374 0.278928717 0.590933793 0.632854328 0.288016657 0.243829176
#> [49] 0.001896251 0.590933793 0.519392422 0.539472286 0.169093772 0.288016657
#> [55] 0.370692148 0.390263950 0.802966706 0.868536815 0.202677666 0.076316728
#> [61] 0.129030643 0.099064346 0.001896251 0.185821814 0.622247223 0.076316728
#> [67] 0.288016657 0.099064346 0.685401855 0.252551342 0.429435086 0.351428440
#> [73] 0.341782599 0.177467855 0.781378396 0.479220563 0.449333861 0.945541036
#> [79] 0.967522235 0.489273167 0.967522235 0.099064346 0.459272371 0.226879753
#> [85] 0.519392422 0.770557094 0.129030643 0.288016657 0.091142622 0.252551342
#> [91] 0.014812434 0.738437743 0.288016657 0.923549315 0.025846596 0.956540319
#> [97] 0.370692148 0.868536815 0.824598120 0.654136893 0.226879753 0.351428440
#> [103] 0.145289859 0.901524648 0.802966706 0.643488418 0.539472286 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 13 26 68 52 129 113 49 184 6 139 129.1 99 60
#> 14.34 15.77 20.62 10.42 23.41 22.86 12.19 17.77 15.64 21.49 23.41 21.19 13.15
#> 96 183 13.1 134 107 106 166 40 125 81 43 79 78
#> 14.54 9.24 14.34 17.81 11.18 16.67 19.98 18.00 15.65 14.06 12.10 16.23 23.88
#> 101 117 128 37 66 25 86 140 63 96.1 125.1 58 36
#> 9.97 17.46 20.35 12.52 22.13 6.32 23.81 12.68 22.77 14.54 15.65 19.34 21.19
#> 128.1 63.1 14 79.1 170 6.1 167 58.1 158 24 6.2 188 100
#> 20.35 22.77 12.89 16.23 19.54 15.64 15.55 19.34 20.14 23.89 15.64 16.16 16.07
#> 90 58.2 8 40.1 42 159 128.2 136 153 139.1 24.1 190 39
#> 20.94 19.34 18.43 18.00 12.43 10.55 20.35 21.83 21.33 21.49 23.89 20.81 15.59
#> 136.1 58.3 139.2 57 166.1 110 97 76 32 37.1 85 111 149
#> 21.83 19.34 21.49 14.46 19.98 17.56 19.14 19.22 20.90 12.52 16.44 17.45 8.37
#> 25.1 5 25.2 139.3 45 150 188.1 177 153.1 58.4 197 166.2 86.1
#> 6.32 16.43 6.32 21.49 17.42 20.33 16.16 12.53 21.33 19.34 21.60 19.98 23.81
#> 123 58.5 187 168 70 8.1 159.1 56 96.2 150.1 97.1 36.1 61
#> 13.00 19.34 9.92 23.72 7.38 18.43 10.55 12.21 14.54 20.33 19.14 21.19 10.12
#> 42.1 18 100.1 84 191 174 185 141 9 22 84.1 67 17
#> 12.43 15.21 16.07 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 148 80 28 98 191.1 182 1 131 176 200 12 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 31 67.1 46.1 142 53 48 178 3 165 144 186 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 160 161 87 20 3.1 44.1 147 137 198 120 44.2 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 83 22.1 53.1 178.1 17.1 148.2 198.1 2 47 31.1 28.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 80.2 132 132.1 53.2 131.1 22.2 17.2 148.3 132.2 31.2 172 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 44.3 165.1 27 72 121 83.1 146 103 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[38]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007618638 0.250305660 -0.166407109
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.26709940 0.02487863 -0.10454917
#> grade_iii, Cure model
#> 0.51797987
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 125 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 154 12.63 1 20 1 0
#> 127 3.53 1 62 0 1
#> 36 21.19 1 48 0 1
#> 68 20.62 1 44 0 0
#> 125.1 15.65 1 67 1 0
#> 5 16.43 1 51 0 1
#> 188 16.16 1 46 0 1
#> 52 10.42 1 52 0 1
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 105 19.75 1 60 0 0
#> 150.1 20.33 1 48 0 0
#> 92 22.92 1 47 0 1
#> 117 17.46 1 26 0 1
#> 69 23.23 1 25 0 1
#> 29 15.45 1 68 1 0
#> 40 18.00 1 28 1 0
#> 199 19.81 1 NA 0 1
#> 4 17.64 1 NA 0 1
#> 45 17.42 1 54 0 1
#> 16 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 108 18.29 1 39 0 1
#> 154.1 12.63 1 20 1 0
#> 6 15.64 1 39 0 0
#> 159 10.55 1 50 0 1
#> 188.1 16.16 1 46 0 1
#> 159.1 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 86 23.81 1 58 0 1
#> 55 19.34 1 69 0 1
#> 4.1 17.64 1 NA 0 1
#> 192 16.44 1 31 1 0
#> 195 11.76 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 86.1 23.81 1 58 0 1
#> 4.2 17.64 1 NA 0 1
#> 192.1 16.44 1 31 1 0
#> 111 17.45 1 47 0 1
#> 86.2 23.81 1 58 0 1
#> 140 12.68 1 59 1 0
#> 171 16.57 1 41 0 1
#> 45.1 17.42 1 54 0 1
#> 128 20.35 1 35 0 1
#> 170 19.54 1 43 0 1
#> 170.1 19.54 1 43 0 1
#> 105.1 19.75 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 45.2 17.42 1 54 0 1
#> 56 12.21 1 60 0 0
#> 69.1 23.23 1 25 0 1
#> 133 14.65 1 57 0 0
#> 85 16.44 1 36 0 0
#> 42 12.43 1 49 0 1
#> 4.3 17.64 1 NA 0 1
#> 114 13.68 1 NA 0 0
#> 179 18.63 1 42 0 0
#> 139 21.49 1 63 1 0
#> 157 15.10 1 47 0 0
#> 158 20.14 1 74 1 0
#> 91.1 5.33 1 61 0 1
#> 15 22.68 1 48 0 0
#> 136 21.83 1 43 0 1
#> 86.3 23.81 1 58 0 1
#> 150.2 20.33 1 48 0 0
#> 195.1 11.76 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 30 17.43 1 78 0 0
#> 179.1 18.63 1 42 0 0
#> 140.1 12.68 1 59 1 0
#> 56.1 12.21 1 60 0 0
#> 184 17.77 1 38 0 0
#> 129 23.41 1 53 1 0
#> 177.1 12.53 1 75 0 0
#> 50 10.02 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 18.1 15.21 1 49 1 0
#> 106 16.67 1 49 1 0
#> 169 22.41 1 46 0 0
#> 190 20.81 1 42 1 0
#> 171.1 16.57 1 41 0 1
#> 164 23.60 1 76 0 1
#> 107 11.18 1 54 1 0
#> 26.1 15.77 1 49 0 1
#> 150.3 20.33 1 48 0 0
#> 41 18.02 1 40 1 0
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 36.1 21.19 1 48 0 1
#> 114.1 13.68 1 NA 0 0
#> 199.1 19.81 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 114.2 13.68 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 14 12.89 1 21 0 0
#> 39.1 15.59 1 37 0 1
#> 175 21.91 1 43 0 0
#> 130.1 16.47 1 53 0 1
#> 168 23.72 1 70 0 0
#> 42.1 12.43 1 49 0 1
#> 190.1 20.81 1 42 1 0
#> 124 9.73 1 NA 1 0
#> 49.2 12.19 1 48 1 0
#> 195.2 11.76 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 121 24.00 0 57 1 0
#> 17 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 148 24.00 0 61 1 0
#> 35 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 38 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 84 24.00 0 39 0 1
#> 31 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 172 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 27 24.00 0 63 1 0
#> 94 24.00 0 51 0 1
#> 11 24.00 0 42 0 1
#> 72 24.00 0 40 0 1
#> 82 24.00 0 34 0 0
#> 191 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 47 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 35.1 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 176 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 38.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 47.1 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 126 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 74 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#> 9 24.00 0 31 1 0
#> 31.1 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 82.1 24.00 0 34 0 0
#> 31.2 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 131 24.00 0 66 0 0
#> 84.1 24.00 0 39 0 1
#> 143 24.00 0 51 0 0
#> 38.2 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 191.1 24.00 0 60 0 1
#> 152 24.00 0 36 0 1
#> 161.1 24.00 0 45 0 0
#> 162 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 132 24.00 0 55 0 0
#> 198 24.00 0 66 0 1
#> 72.1 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 156.1 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 156.2 24.00 0 50 1 0
#> 156.3 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 74.2 24.00 0 43 0 1
#> 172.1 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 119.2 24.00 0 17 0 0
#> 185.1 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 74.3 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 11.1 24.00 0 42 0 1
#> 27.1 24.00 0 63 1 0
#> 152.1 24.00 0 36 0 1
#> 132.1 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 27.2 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 104.1 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 47.2 24.00 0 38 0 1
#> 47.3 24.00 0 38 0 1
#> 132.2 24.00 0 55 0 0
#> 67.1 24.00 0 25 0 0
#> 54 24.00 0 53 1 0
#> 185.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.27 NA NA NA
#> 2 age, Cure model 0.0249 NA NA NA
#> 3 grade_ii, Cure model -0.105 NA NA NA
#> 4 grade_iii, Cure model 0.518 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00762 NA NA NA
#> 2 grade_ii, Survival model 0.250 NA NA NA
#> 3 grade_iii, Survival model -0.166 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.26710 0.02488 -0.10455 0.51798
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253.4
#> Residual Deviance: 246.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.26709940 0.02487863 -0.10454917 0.51797987
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007618638 0.250305660 -0.166407109
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.757806077 0.508488268 0.584553090 0.730858389 0.984992946 0.079676986
#> [7] 0.117943424 0.508488268 0.447749064 0.459718757 0.926156081 0.142232915
#> [13] 0.483847178 0.184108831 0.142232915 0.033000587 0.291723701 0.022933726
#> [19] 0.571589673 0.271178928 0.323481689 0.940729626 0.649881339 0.250720739
#> [25] 0.730858389 0.533406132 0.897431255 0.459718757 0.897431255 0.955418554
#> [31] 0.001463108 0.221144116 0.413174459 0.546091152 0.001463108 0.413174459
#> [37] 0.302155981 0.001463108 0.703808208 0.367274393 0.323481689 0.133848317
#> [43] 0.202295830 0.202295830 0.184108831 0.117943424 0.323481689 0.812952789
#> [49] 0.022933726 0.636608161 0.413174459 0.785177480 0.230992435 0.072352821
#> [55] 0.610323428 0.175114076 0.955418554 0.038892174 0.058189292 0.001463108
#> [61] 0.142232915 0.676722546 0.312737390 0.230992435 0.703808208 0.812952789
#> [67] 0.281404171 0.017965806 0.757806077 0.841080749 0.584553090 0.356034060
#> [73] 0.045071791 0.102628901 0.367274393 0.013192765 0.883146368 0.483847178
#> [79] 0.142232915 0.260939186 0.389930854 0.079676986 0.841080749 0.094747052
#> [85] 0.690245731 0.546091152 0.051513533 0.389930854 0.009187525 0.785177480
#> [91] 0.102628901 0.841080749 0.623431763 0.663247757 0.065178174 0.000000000
#> [97] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 177 125 18 154 127 36 68 125.1 5 188 52 150 26
#> 12.53 15.65 15.21 12.63 3.53 21.19 20.62 15.65 16.43 16.16 10.42 20.33 15.77
#> 105 150.1 92 117 69 29 40 45 16 96 108 154.1 6
#> 19.75 20.33 22.92 17.46 23.23 15.45 18.00 17.42 8.71 14.54 18.29 12.63 15.64
#> 159 188.1 159.1 91 86 55 192 39 86.1 192.1 111 86.2 140
#> 10.55 16.16 10.55 5.33 23.81 19.34 16.44 15.59 23.81 16.44 17.45 23.81 12.68
#> 171 45.1 128 170 170.1 105.1 68.1 45.2 56 69.1 133 85 42
#> 16.57 17.42 20.35 19.54 19.54 19.75 20.62 17.42 12.21 23.23 14.65 16.44 12.43
#> 179 139 157 158 91.1 15 136 86.3 150.2 155 30 179.1 140.1
#> 18.63 21.49 15.10 20.14 5.33 22.68 21.83 23.81 20.33 13.08 17.43 18.63 12.68
#> 56.1 184 129 177.1 49 18.1 106 169 190 171.1 164 107 26.1
#> 12.21 17.77 23.41 12.53 12.19 15.21 16.67 22.41 20.81 16.57 23.60 11.18 15.77
#> 150.3 41 130 36.1 49.1 32 14 39.1 175 130.1 168 42.1 190.1
#> 20.33 18.02 16.47 21.19 12.19 20.90 12.89 15.59 21.91 16.47 23.72 12.43 20.81
#> 49.2 180 57 197 121 17 147 148 35 156 38 161 84
#> 12.19 14.82 14.46 21.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 34 172 141 119 27 94 11 72 82 191 116 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 35.1 173 176 21 38.1 104 47.1 200 126 163 80 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 9 31.1 103 82.1 31.2 186 112 131 84.1 143 38.2 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 152 161.1 162 34.1 132 198 72.1 144 156.1 7 156.2 156.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 67 74.2 172.1 185 119.2 185.1 141.1 74.3 118 148.1 11.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 132.1 137 27.2 162.1 104.1 182 146 47.2 47.3 132.2 67.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.2
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[39]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003021454 0.659162242 0.781504782
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.736176638 0.014069726 0.001551131
#> grade_iii, Cure model
#> 0.655004691
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 89 11.44 1 NA 0 0
#> 93 10.33 1 52 0 1
#> 128 20.35 1 35 0 1
#> 8 18.43 1 32 0 0
#> 171 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 15 22.68 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 181 16.46 1 45 0 1
#> 39 15.59 1 37 0 1
#> 101 9.97 1 10 0 1
#> 59 10.16 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 128.1 20.35 1 35 0 1
#> 96 14.54 1 33 0 1
#> 26 15.77 1 49 0 1
#> 42 12.43 1 49 0 1
#> 14 12.89 1 21 0 0
#> 117 17.46 1 26 0 1
#> 183 9.24 1 67 1 0
#> 36 21.19 1 48 0 1
#> 133 14.65 1 57 0 0
#> 114 13.68 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 63 22.77 1 31 1 0
#> 169 22.41 1 46 0 0
#> 183.1 9.24 1 67 1 0
#> 51.1 18.23 1 83 0 1
#> 45 17.42 1 54 0 1
#> 180 14.82 1 37 0 0
#> 195 11.76 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 114.1 13.68 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 89.1 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 127 3.53 1 62 0 1
#> 150 20.33 1 48 0 0
#> 56 12.21 1 60 0 0
#> 78.1 23.88 1 43 0 0
#> 180.1 14.82 1 37 0 0
#> 181.1 16.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 171.1 16.57 1 41 0 1
#> 37 12.52 1 57 1 0
#> 4 17.64 1 NA 0 1
#> 18.1 15.21 1 49 1 0
#> 180.2 14.82 1 37 0 0
#> 105 19.75 1 60 0 0
#> 154 12.63 1 20 1 0
#> 55 19.34 1 69 0 1
#> 127.1 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 197 21.60 1 69 1 0
#> 100 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 45.1 17.42 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 79 16.23 1 54 1 0
#> 4.1 17.64 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 88 18.37 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 52 10.42 1 52 0 1
#> 166 19.98 1 48 0 0
#> 49 12.19 1 48 1 0
#> 190.1 20.81 1 42 1 0
#> 169.1 22.41 1 46 0 0
#> 195.1 11.76 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 158 20.14 1 74 1 0
#> 149 8.37 1 33 1 0
#> 23 16.92 1 61 0 0
#> 134 17.81 1 47 1 0
#> 168 23.72 1 70 0 0
#> 5 16.43 1 51 0 1
#> 101.1 9.97 1 10 0 1
#> 16 8.71 1 71 0 1
#> 175 21.91 1 43 0 0
#> 8.1 18.43 1 32 0 0
#> 125 15.65 1 67 1 0
#> 8.2 18.43 1 32 0 0
#> 5.1 16.43 1 51 0 1
#> 117.1 17.46 1 26 0 1
#> 192 16.44 1 31 1 0
#> 91.1 5.33 1 61 0 1
#> 189.2 10.51 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 101.2 9.97 1 10 0 1
#> 92 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 41 18.02 1 40 1 0
#> 113.1 22.86 1 34 0 0
#> 100.1 16.07 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 45.2 17.42 1 54 0 1
#> 76 19.22 1 54 0 1
#> 183.2 9.24 1 67 1 0
#> 26.1 15.77 1 49 0 1
#> 40 18.00 1 28 1 0
#> 18.2 15.21 1 49 1 0
#> 166.1 19.98 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 60 13.15 1 38 1 0
#> 105.1 19.75 1 60 0 0
#> 30 17.43 1 78 0 0
#> 188 16.16 1 46 0 1
#> 66 22.13 1 53 0 0
#> 131 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 156 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 2 24.00 0 9 0 0
#> 75 24.00 0 21 1 0
#> 98 24.00 0 34 1 0
#> 137 24.00 0 45 1 0
#> 142 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 160.1 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 147 24.00 0 76 1 0
#> 185 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 9 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 172.1 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 198.1 24.00 0 66 0 1
#> 152 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 137.1 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 162 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 147.1 24.00 0 76 1 0
#> 53 24.00 0 32 0 1
#> 104 24.00 0 50 1 0
#> 84 24.00 0 39 0 1
#> 135 24.00 0 58 1 0
#> 80 24.00 0 41 0 0
#> 152.1 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 160.2 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 71 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 67 24.00 0 25 0 0
#> 172.2 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 80.1 24.00 0 41 0 0
#> 185.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 173.1 24.00 0 19 0 1
#> 2.1 24.00 0 9 0 0
#> 172.3 24.00 0 41 0 0
#> 198.2 24.00 0 66 0 1
#> 31 24.00 0 36 0 1
#> 53.1 24.00 0 32 0 1
#> 104.1 24.00 0 50 1 0
#> 53.2 24.00 0 32 0 1
#> 83.1 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 176.1 24.00 0 43 0 1
#> 144.1 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 165.2 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 47 24.00 0 38 0 1
#> 121.2 24.00 0 57 1 0
#> 12.1 24.00 0 63 0 0
#> 75.1 24.00 0 21 1 0
#> 176.2 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 104.2 24.00 0 50 1 0
#> 17.1 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 174 24.00 0 49 1 0
#> 73 24.00 0 NA 0 1
#> 135.1 24.00 0 58 1 0
#> 141 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.736 NA NA NA
#> 2 age, Cure model 0.0141 NA NA NA
#> 3 grade_ii, Cure model 0.00155 NA NA NA
#> 4 grade_iii, Cure model 0.655 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00302 NA NA NA
#> 2 grade_ii, Survival model 0.659 NA NA NA
#> 3 grade_iii, Survival model 0.782 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.736177 0.014070 0.001551 0.655005
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 251.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.736176638 0.014069726 0.001551131 0.655004691
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003021454 0.659162242 0.781504782
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90530306 0.35566105 0.46131527 0.61562677 0.27460224 0.17380915
#> [7] 0.07675987 0.63312701 0.74044647 0.91240592 0.96691568 0.01664623
#> [13] 0.65019930 0.35566105 0.81683027 0.71645196 0.86172055 0.83942181
#> [19] 0.55185440 0.93301435 0.27460224 0.80917443 0.50225717 0.14611495
#> [25] 0.18842130 0.93301435 0.50225717 0.57987896 0.78645719 0.88369758
#> [31] 0.76380920 0.31002676 0.98689107 0.37678399 0.86905309 0.01664623
#> [37] 0.78645719 0.63312701 0.34427531 0.61562677 0.85433244 0.76380920
#> [43] 0.78645719 0.41919053 0.84690402 0.44042440 0.98689107 0.11380321
#> [49] 0.24716271 0.70012892 0.32197072 0.57987896 0.14611495 0.68368518
#> [55] 0.97363929 0.49183632 0.74044647 0.89815154 0.39813371 0.87639590
#> [61] 0.32197072 0.18842130 0.89095031 0.38753908 0.96015709 0.60657244
#> [67] 0.54213251 0.05198338 0.66712557 0.91240592 0.95336264 0.23205869
#> [73] 0.46131527 0.73245273 0.46131527 0.66712557 0.55185440 0.65019930
#> [79] 0.97363929 0.82441662 0.91240592 0.09684592 0.75602855 0.52230638
#> [85] 0.11380321 0.70012892 0.27460224 0.57987896 0.45097335 0.93301435
#> [91] 0.71645196 0.53229110 0.76380920 0.39813371 0.24716271 0.83194369
#> [97] 0.41919053 0.57046433 0.69195107 0.21707380 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 93 128 8 171 99 15 164 181 39 101 25 78 85
#> 10.33 20.35 18.43 16.57 21.19 22.68 23.60 16.46 15.59 9.97 6.32 23.88 16.44
#> 128.1 96 26 42 14 117 183 36 133 51 63 169 183.1
#> 20.35 14.54 15.77 12.43 12.89 17.46 9.24 21.19 14.65 18.23 22.77 22.41 9.24
#> 51.1 45 180 43 18 32 127 150 56 78.1 180.1 181.1 68
#> 18.23 17.42 14.82 12.10 15.21 20.90 3.53 20.33 12.21 23.88 14.82 16.46 20.62
#> 171.1 37 18.1 180.2 105 154 55 127.1 113 197 100 190 45.1
#> 16.57 12.52 15.21 14.82 19.75 12.63 19.34 3.53 22.86 21.60 16.07 20.81 17.42
#> 63.1 79 91 88 39.1 52 166 49 190.1 169.1 159 158 149
#> 22.77 16.23 5.33 18.37 15.59 10.42 19.98 12.19 20.81 22.41 10.55 20.14 8.37
#> 23 134 168 5 101.1 16 175 8.1 125 8.2 5.1 117.1 192
#> 16.92 17.81 23.72 16.43 9.97 8.71 21.91 18.43 15.65 18.43 16.43 17.46 16.44
#> 91.1 13 101.2 92 167 41 113.1 100.1 36.1 45.2 76 183.2 26.1
#> 5.33 14.34 9.97 22.92 15.55 18.02 22.86 16.07 21.19 17.42 19.22 9.24 15.77
#> 40 18.2 166.1 197.1 60 105.1 30 188 66 131 120 156 46
#> 18.00 15.21 19.98 21.60 13.15 19.75 17.43 16.16 22.13 24.00 24.00 24.00 24.00
#> 165 54 2 75 98 137 142 160 172 83 64 12 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 98.1 147 185 82 9 165.1 172.1 198 65 121 144 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 176 137.1 109 162 120.1 147.1 53 104 84 135 80 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 160.2 161.1 71 173 67 172.2 122 132 80.1 185.1 112 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 172.3 198.2 31 53.1 104.1 53.2 83.1 33 200 176.1 144.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.2 48 121.1 191 47 121.2 12.1 75.1 176.2 196 62 104.2 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 174 135.1 141 126
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[40]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01428816 0.37016821 0.38099898
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.31127820 0.01543184 0.63358882
#> grade_iii, Cure model
#> 1.70543340
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 61 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 133 14.65 1 57 0 0
#> 124 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 42 12.43 1 49 0 1
#> 171 16.57 1 41 0 1
#> 43 12.10 1 61 0 1
#> 96 14.54 1 33 0 1
#> 150 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 61.1 10.12 1 36 0 1
#> 155 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 63 22.77 1 31 1 0
#> 180 14.82 1 37 0 0
#> 30 17.43 1 78 0 0
#> 107 11.18 1 54 1 0
#> 127 3.53 1 62 0 1
#> 57 14.46 1 45 0 1
#> 23 16.92 1 61 0 0
#> 66 22.13 1 53 0 0
#> 79 16.23 1 54 1 0
#> 5 16.43 1 51 0 1
#> 164 23.60 1 76 0 1
#> 30.1 17.43 1 78 0 0
#> 4 17.64 1 NA 0 1
#> 85 16.44 1 36 0 0
#> 25.1 6.32 1 34 1 0
#> 81 14.06 1 34 0 0
#> 29 15.45 1 68 1 0
#> 61.2 10.12 1 36 0 1
#> 45 17.42 1 54 0 1
#> 96.1 14.54 1 33 0 1
#> 43.1 12.10 1 61 0 1
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 41 18.02 1 40 1 0
#> 15 22.68 1 48 0 0
#> 55 19.34 1 69 0 1
#> 89 11.44 1 NA 0 0
#> 124.1 9.73 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 81.1 14.06 1 34 0 0
#> 157 15.10 1 47 0 0
#> 139 21.49 1 63 1 0
#> 76 19.22 1 54 0 1
#> 155.1 13.08 1 26 0 0
#> 92 22.92 1 47 0 1
#> 45.1 17.42 1 54 0 1
#> 175 21.91 1 43 0 0
#> 97 19.14 1 65 0 1
#> 77 7.27 1 67 0 1
#> 105 19.75 1 60 0 0
#> 159 10.55 1 50 0 1
#> 181 16.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 77.1 7.27 1 67 0 1
#> 177 12.53 1 75 0 0
#> 170 19.54 1 43 0 1
#> 23.1 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 114.1 13.68 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 55.1 19.34 1 69 0 1
#> 195 11.76 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 32 20.90 1 37 1 0
#> 32.1 20.90 1 37 1 0
#> 129 23.41 1 53 1 0
#> 29.1 15.45 1 68 1 0
#> 16 8.71 1 71 0 1
#> 24 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 159.1 10.55 1 50 0 1
#> 181.1 16.46 1 45 0 1
#> 199.1 19.81 1 NA 0 1
#> 5.1 16.43 1 51 0 1
#> 188 16.16 1 46 0 1
#> 107.1 11.18 1 54 1 0
#> 164.1 23.60 1 76 0 1
#> 96.2 14.54 1 33 0 1
#> 107.2 11.18 1 54 1 0
#> 164.2 23.60 1 76 0 1
#> 89.1 11.44 1 NA 0 0
#> 92.1 22.92 1 47 0 1
#> 117 17.46 1 26 0 1
#> 140.1 12.68 1 59 1 0
#> 157.1 15.10 1 47 0 0
#> 125 15.65 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 101.1 9.97 1 10 0 1
#> 4.1 17.64 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 106 16.67 1 49 1 0
#> 29.2 15.45 1 68 1 0
#> 4.2 17.64 1 NA 0 1
#> 32.2 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 125.1 15.65 1 67 1 0
#> 167 15.55 1 56 1 0
#> 167.1 15.55 1 56 1 0
#> 14 12.89 1 21 0 0
#> 199.2 19.81 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 77.2 7.27 1 67 0 1
#> 133.1 14.65 1 57 0 0
#> 8 18.43 1 32 0 0
#> 13.1 14.34 1 54 0 1
#> 119 24.00 0 17 0 0
#> 71 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 27 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 80 24.00 0 41 0 0
#> 31.1 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 35.1 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 185 24.00 0 44 1 0
#> 72.2 24.00 0 40 0 1
#> 22.1 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 163 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 2.1 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 82 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 162 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 142 24.00 0 53 0 0
#> 71.1 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 80.1 24.00 0 41 0 0
#> 137.1 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 33 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 200 24.00 0 64 0 0
#> 3.1 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 109.1 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 11 24.00 0 42 0 1
#> 138 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 72.3 24.00 0 40 0 1
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 112.1 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 152 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 162.1 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 35.2 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 119.1 24.00 0 17 0 0
#> 132 24.00 0 55 0 0
#> 48 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 38 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 119.2 24.00 0 17 0 0
#> 11.1 24.00 0 42 0 1
#> 132.1 24.00 0 55 0 0
#> 94 24.00 0 51 0 1
#> 112.2 24.00 0 61 0 0
#> 131 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 172.1 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 73.2 24.00 0 NA 0 1
#> 112.3 24.00 0 61 0 0
#> 151.1 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 62.1 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 138.1 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 35.3 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.31 NA NA NA
#> 2 age, Cure model 0.0154 NA NA NA
#> 3 grade_ii, Cure model 0.634 NA NA NA
#> 4 grade_iii, Cure model 1.71 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0143 NA NA NA
#> 2 grade_ii, Survival model 0.370 NA NA NA
#> 3 grade_iii, Survival model 0.381 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.31128 0.01543 0.63359 1.70543
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 252.8
#> Residual Deviance: 229.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.31127820 0.01543184 0.63358882 1.70543340
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01428816 0.37016821 0.38099898
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8247213769 0.9552685461 0.4518790698 0.2450433180 0.7114833416
#> [6] 0.2352221070 0.7254257783 0.4766147634 0.0752074889 0.5386402164
#> [11] 0.8247213769 0.6033809845 0.3486047523 0.0216546347 0.4397135362
#> [16] 0.1713702368 0.7534565185 0.9849534337 0.5134790227 0.2066299167
#> [21] 0.0306133132 0.3056998796 0.2851102959 0.0029612224 0.1713702368
#> [26] 0.2748447166 0.9552685461 0.5641874041 0.3818430623 0.8247213769
#> [31] 0.1887335032 0.4766147634 0.7254257783 0.0411381308 0.5901877475
#> [36] 0.1465558536 0.0259419029 0.0948831687 0.5134790227 0.5641874041
#> [41] 0.4159848591 0.0467336905 0.1154921368 0.6033809845 0.0140273386
#> [46] 0.1887335032 0.0356974959 0.1229699110 0.9112372706 0.0815336504
#> [51] 0.7958849807 0.2549895741 0.9112372706 0.6976151608 0.0881557176
#> [56] 0.2066299167 0.6567740881 0.0948831687 0.0948831687 0.1384884543
#> [61] 0.0691349953 0.0526196971 0.0526196971 0.0101705869 0.3818430623
#> [66] 0.8966316105 0.0001846331 0.0010322001 0.7958849807 0.2549895741
#> [71] 0.2851102959 0.3162941455 0.7534565185 0.0029612224 0.4766147634
#> [76] 0.7534565185 0.0029612224 0.0140273386 0.1630396860 0.6567740881
#> [81] 0.4159848591 0.3269747907 0.8678762101 0.8678762101 0.6298341394
#> [86] 0.2254763057 0.3818430623 0.0526196971 0.6839259231 0.3269747907
#> [91] 0.3596406866 0.3596406866 0.6432675524 0.1547051609 0.9112372706
#> [96] 0.4518790698 0.1306445949 0.5386402164 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 61 25 133 130 42 171 43 96 150 13 61.1 155 39
#> 10.12 6.32 14.65 16.47 12.43 16.57 12.10 14.54 20.33 14.34 10.12 13.08 15.59
#> 63 180 30 107 127 57 23 66 79 5 164 30.1 85
#> 22.77 14.82 17.43 11.18 3.53 14.46 16.92 22.13 16.23 16.43 23.60 17.43 16.44
#> 25.1 81 29 61.2 45 96.1 43.1 136 60 41 15 55 57.1
#> 6.32 14.06 15.45 10.12 17.42 14.54 12.10 21.83 13.15 18.02 22.68 19.34 14.46
#> 81.1 157 139 76 155.1 92 45.1 175 97 77 105 159 181
#> 14.06 15.10 21.49 19.22 13.08 22.92 17.42 21.91 19.14 7.27 19.75 10.55 16.46
#> 77.1 177 170 23.1 140 58 55.1 88 128 32 32.1 129 29.1
#> 7.27 12.53 19.54 16.92 12.68 19.34 19.34 18.37 20.35 20.90 20.90 23.41 15.45
#> 16 24 168 159.1 181.1 5.1 188 107.1 164.1 96.2 107.2 164.2 92.1
#> 8.71 23.89 23.72 10.55 16.46 16.43 16.16 11.18 23.60 14.54 11.18 23.60 22.92
#> 117 140.1 157.1 125 101 101.1 123 106 29.2 32.2 154 125.1 167
#> 17.46 12.68 15.10 15.65 9.97 9.97 13.00 16.67 15.45 20.90 12.63 15.65 15.55
#> 167.1 14 110 77.2 133.1 8 13.1 119 71 72 116 27 22
#> 15.55 12.89 17.56 7.27 14.65 18.43 14.34 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 31 35 1 80 31.1 196 35.1 72.1 185 72.2 22.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 143 21 2 2.1 109 3 28 82 162 191 142 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 137.1 112 33 122 185.1 118 34 200 3.1 161 109.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 138 28.1 62 72.3 147 147.1 112.1 20 152 151 162.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.2 44 102 119.1 132 48 84 38 103 119.2 11.1 132.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.2 131 172 173 172.1 160 112.3 151.1 193 62.1 148 138.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.3
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[41]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.02106556 1.02240135 0.29640656
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.247661082 0.002891102 -0.059099616
#> grade_iii, Cure model
#> 1.045513999
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 69 23.23 1 25 0 1
#> 188 16.16 1 46 0 1
#> 16 8.71 1 71 0 1
#> 124 9.73 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 16.1 8.71 1 71 0 1
#> 85 16.44 1 36 0 0
#> 107 11.18 1 54 1 0
#> 56 12.21 1 60 0 0
#> 36 21.19 1 48 0 1
#> 124.1 9.73 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 101 9.97 1 10 0 1
#> 55 19.34 1 69 0 1
#> 106 16.67 1 49 1 0
#> 18 15.21 1 49 1 0
#> 5 16.43 1 51 0 1
#> 70.1 7.38 1 30 1 0
#> 13 14.34 1 54 0 1
#> 167.1 15.55 1 56 1 0
#> 166 19.98 1 48 0 0
#> 100 16.07 1 60 0 0
#> 91 5.33 1 61 0 1
#> 26 15.77 1 49 0 1
#> 169 22.41 1 46 0 0
#> 10 10.53 1 34 0 0
#> 30 17.43 1 78 0 0
#> 136 21.83 1 43 0 1
#> 81 14.06 1 34 0 0
#> 15 22.68 1 48 0 0
#> 69.1 23.23 1 25 0 1
#> 111 17.45 1 47 0 1
#> 24.1 23.89 1 38 0 0
#> 37 12.52 1 57 1 0
#> 192 16.44 1 31 1 0
#> 125 15.65 1 67 1 0
#> 194 22.40 1 38 0 1
#> 166.1 19.98 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 79 16.23 1 54 1 0
#> 30.1 17.43 1 78 0 0
#> 16.2 8.71 1 71 0 1
#> 194.1 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 96 14.54 1 33 0 1
#> 167.2 15.55 1 56 1 0
#> 52 10.42 1 52 0 1
#> 81.1 14.06 1 34 0 0
#> 23 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 188.1 16.16 1 46 0 1
#> 194.2 22.40 1 38 0 1
#> 128 20.35 1 35 0 1
#> 68 20.62 1 44 0 0
#> 60 13.15 1 38 1 0
#> 108 18.29 1 39 0 1
#> 6 15.64 1 39 0 0
#> 30.2 17.43 1 78 0 0
#> 113 22.86 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 66 22.13 1 53 0 0
#> 15.1 22.68 1 48 0 0
#> 181 16.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 70.2 7.38 1 30 1 0
#> 23.1 16.92 1 61 0 0
#> 106.1 16.67 1 49 1 0
#> 58 19.34 1 39 0 0
#> 78 23.88 1 43 0 0
#> 91.1 5.33 1 61 0 1
#> 149 8.37 1 33 1 0
#> 86 23.81 1 58 0 1
#> 199 19.81 1 NA 0 1
#> 128.1 20.35 1 35 0 1
#> 159 10.55 1 50 0 1
#> 90 20.94 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 128.2 20.35 1 35 0 1
#> 23.2 16.92 1 61 0 0
#> 26.1 15.77 1 49 0 1
#> 37.1 12.52 1 57 1 0
#> 42 12.43 1 49 0 1
#> 63 22.77 1 31 1 0
#> 108.1 18.29 1 39 0 1
#> 37.2 12.52 1 57 1 0
#> 199.1 19.81 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 61 10.12 1 36 0 1
#> 14 12.89 1 21 0 0
#> 90.1 20.94 1 50 0 1
#> 108.2 18.29 1 39 0 1
#> 57.1 14.46 1 45 0 1
#> 63.1 22.77 1 31 1 0
#> 90.2 20.94 1 50 0 1
#> 76 19.22 1 54 0 1
#> 81.2 14.06 1 34 0 0
#> 70.3 7.38 1 30 1 0
#> 97.1 19.14 1 65 0 1
#> 91.2 5.33 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 155 13.08 1 26 0 0
#> 149.1 8.37 1 33 1 0
#> 107.1 11.18 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 56.1 12.21 1 60 0 0
#> 88 18.37 1 47 0 0
#> 40 18.00 1 28 1 0
#> 155.1 13.08 1 26 0 0
#> 48 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 142 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 34 24.00 0 36 0 0
#> 64.1 24.00 0 43 0 0
#> 82 24.00 0 34 0 0
#> 122 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 162 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 146 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 178 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 178.1 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 191 24.00 0 60 0 1
#> 46.1 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 28.1 24.00 0 67 1 0
#> 182 24.00 0 35 0 0
#> 151 24.00 0 42 0 0
#> 3 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 120.1 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 67.1 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 162.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 38 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 148 24.00 0 61 1 0
#> 34.1 24.00 0 36 0 0
#> 72 24.00 0 40 0 1
#> 17 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 3.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 19 24.00 0 57 0 1
#> 186.1 24.00 0 45 1 0
#> 44.2 24.00 0 56 0 0
#> 82.1 24.00 0 34 0 0
#> 160.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 193.1 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 132 24.00 0 55 0 0
#> 138.1 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 82.2 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 83 24.00 0 6 0 0
#> 160.2 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 11.1 24.00 0 42 0 1
#> 118.1 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 193.2 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 182.1 24.00 0 35 0 0
#> 11.2 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 73 24.00 0 NA 0 1
#> 131 24.00 0 66 0 0
#> 21.1 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.248 NA NA NA
#> 2 age, Cure model 0.00289 NA NA NA
#> 3 grade_ii, Cure model -0.0591 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0211 NA NA NA
#> 2 grade_ii, Survival model 1.02 NA NA NA
#> 3 grade_iii, Survival model 0.296 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.247661 0.002891 -0.059100 1.045514
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 251.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.247661082 0.002891102 -0.059099616 1.045513999
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.02106556 1.02240135 0.29640656
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2000300 0.3950277 0.8461692 0.9732317 0.9847990 0.9732317 0.8285384
#> [8] 0.9479577 0.9370226 0.6132377 0.8740812 0.9683484 0.7043923 0.8145481
#> [15] 0.8843217 0.8374970 0.9847990 0.8974813 0.8740812 0.6878188 0.8544379
#> [22] 0.9935752 0.8585319 0.5373918 0.9557107 0.7833831 0.6016180 0.9007015
#> [29] 0.5069294 0.3950277 0.7775176 0.2000300 0.9257349 0.8285384 0.8664901
#> [36] 0.5521512 0.6878188 0.7043923 0.8419187 0.7833831 0.9732317 0.5521512
#> [43] 0.8909780 0.9425514 0.8876604 0.8740812 0.9608218 0.9007015 0.7993625
#> [50] 0.9226685 0.8461692 0.5521512 0.6620290 0.6526475 0.9102213 0.7531534
#> [57] 0.8702962 0.7833831 0.4474642 0.9557107 0.5894513 0.5069294 0.8239095
#> [64] 0.7334963 0.9847990 0.7993625 0.8145481 0.7043923 0.3134298 0.9935752
#> [71] 0.9802285 0.3621047 0.6620290 0.9531374 0.6242924 0.6620290 0.7993625
#> [78] 0.8585319 0.9257349 0.9342120 0.4728920 0.7531534 0.9257349 0.9708064
#> [85] 0.9633603 0.9195623 0.6242924 0.7531534 0.8909780 0.4728920 0.6242924
#> [92] 0.7263386 0.9007015 0.9847990 0.7334963 0.9935752 0.9425514 0.9133489
#> [99] 0.9802285 0.9479577 0.9658863 0.9370226 0.7466464 0.7715338 0.9133489
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000
#>
#> $Time
#> 24 69 188 16 70 16.1 85 107 56 36 167 101 55
#> 23.89 23.23 16.16 8.71 7.38 8.71 16.44 11.18 12.21 21.19 15.55 9.97 19.34
#> 106 18 5 70.1 13 167.1 166 100 91 26 169 10 30
#> 16.67 15.21 16.43 7.38 14.34 15.55 19.98 16.07 5.33 15.77 22.41 10.53 17.43
#> 136 81 15 69.1 111 24.1 37 192 125 194 166.1 55.1 79
#> 21.83 14.06 22.68 23.23 17.45 23.89 12.52 16.44 15.65 22.40 19.98 19.34 16.23
#> 30.1 16.2 194.1 57 43 96 167.2 52 81.1 23 177 188.1 194.2
#> 17.43 8.71 22.40 14.46 12.10 14.54 15.55 10.42 14.06 16.92 12.53 16.16 22.40
#> 128 68 60 108 6 30.2 113 10.1 66 15.1 181 97 70.2
#> 20.35 20.62 13.15 18.29 15.64 17.43 22.86 10.53 22.13 22.68 16.46 19.14 7.38
#> 23.1 106.1 58 78 91.1 149 86 128.1 159 90 128.2 23.2 26.1
#> 16.92 16.67 19.34 23.88 5.33 8.37 23.81 20.35 10.55 20.94 20.35 16.92 15.77
#> 37.1 42 63 108.1 37.2 187 61 14 90.1 108.2 57.1 63.1 90.2
#> 12.52 12.43 22.77 18.29 12.52 9.92 10.12 12.89 20.94 18.29 14.46 22.77 20.94
#> 76 81.2 70.3 97.1 91.2 43.1 155 149.1 107.1 145 56.1 88 40
#> 19.22 14.06 7.38 19.14 5.33 12.10 13.08 8.37 11.18 10.07 12.21 18.37 18.00
#> 155.1 48 64 142 9 46 95 12 34 64.1 82 122 186
#> 13.08 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 160 141 118 126 162 28 146 1 178 80 178.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 191 46.1 11 28.1 182 151 3 120 67 120.1 21 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 138 152 162.1 44 38 193 143 161 148 34.1 72 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 3.1 71 44.1 19 186.1 44.2 82.1 160.1 65 193.1 147 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 146.1 84 82.2 116 83 160.2 137 33 53 11.1 118.1 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.2 196 182.1 11.2 109 143.1 98 131 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[42]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01553253 0.62362335 0.40264514
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.36491695 0.02484497 0.14280906
#> grade_iii, Cure model
#> 1.16536534
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 63 22.77 1 31 1 0
#> 101 9.97 1 10 0 1
#> 106 16.67 1 49 1 0
#> 18 15.21 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 55 19.34 1 69 0 1
#> 13 14.34 1 54 0 1
#> 32 20.90 1 37 1 0
#> 66 22.13 1 53 0 0
#> 97 19.14 1 65 0 1
#> 29 15.45 1 68 1 0
#> 6 15.64 1 39 0 0
#> 199 19.81 1 NA 0 1
#> 171 16.57 1 41 0 1
#> 92 22.92 1 47 0 1
#> 43 12.10 1 61 0 1
#> 159 10.55 1 50 0 1
#> 90 20.94 1 50 0 1
#> 58 19.34 1 39 0 0
#> 195 11.76 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 77 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 49.1 12.19 1 48 1 0
#> 154 12.63 1 20 1 0
#> 49.2 12.19 1 48 1 0
#> 10 10.53 1 34 0 0
#> 60 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 158 20.14 1 74 1 0
#> 13.1 14.34 1 54 0 1
#> 18.1 15.21 1 49 1 0
#> 175 21.91 1 43 0 0
#> 41 18.02 1 40 1 0
#> 168 23.72 1 70 0 0
#> 181 16.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 168.1 23.72 1 70 0 0
#> 192 16.44 1 31 1 0
#> 139 21.49 1 63 1 0
#> 130 16.47 1 53 0 1
#> 10.1 10.53 1 34 0 0
#> 52 10.42 1 52 0 1
#> 55.1 19.34 1 69 0 1
#> 157 15.10 1 47 0 0
#> 51 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 157.1 15.10 1 47 0 0
#> 195.1 11.76 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 59 10.16 1 NA 1 0
#> 168.2 23.72 1 70 0 0
#> 181.1 16.46 1 45 0 1
#> 51.1 18.23 1 83 0 1
#> 171.1 16.57 1 41 0 1
#> 130.1 16.47 1 53 0 1
#> 171.2 16.57 1 41 0 1
#> 107 11.18 1 54 1 0
#> 63.1 22.77 1 31 1 0
#> 159.1 10.55 1 50 0 1
#> 133 14.65 1 57 0 0
#> 29.1 15.45 1 68 1 0
#> 14 12.89 1 21 0 0
#> 133.1 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 194 22.40 1 38 0 1
#> 179 18.63 1 42 0 0
#> 128 20.35 1 35 0 1
#> 107.1 11.18 1 54 1 0
#> 18.2 15.21 1 49 1 0
#> 167 15.55 1 56 1 0
#> 107.2 11.18 1 54 1 0
#> 18.3 15.21 1 49 1 0
#> 179.1 18.63 1 42 0 0
#> 164.1 23.60 1 76 0 1
#> 25 6.32 1 34 1 0
#> 110 17.56 1 65 0 1
#> 105 19.75 1 60 0 0
#> 23 16.92 1 61 0 0
#> 111 17.45 1 47 0 1
#> 88.1 18.37 1 47 0 0
#> 187 9.92 1 39 1 0
#> 88.2 18.37 1 47 0 0
#> 128.1 20.35 1 35 0 1
#> 199.1 19.81 1 NA 0 1
#> 159.2 10.55 1 50 0 1
#> 6.1 15.64 1 39 0 0
#> 128.2 20.35 1 35 0 1
#> 108 18.29 1 39 0 1
#> 56 12.21 1 60 0 0
#> 108.1 18.29 1 39 0 1
#> 155 13.08 1 26 0 0
#> 29.2 15.45 1 68 1 0
#> 130.2 16.47 1 53 0 1
#> 150 20.33 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 97.1 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 26 15.77 1 49 0 1
#> 168.3 23.72 1 70 0 0
#> 181.2 16.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 159.3 10.55 1 50 0 1
#> 45 17.42 1 54 0 1
#> 52.1 10.42 1 52 0 1
#> 180 14.82 1 37 0 0
#> 99 21.19 1 38 0 1
#> 70 7.38 1 30 1 0
#> 59.1 10.16 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 64 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 98 24.00 0 34 1 0
#> 156 24.00 0 50 1 0
#> 44 24.00 0 56 0 0
#> 173 24.00 0 19 0 1
#> 33 24.00 0 53 0 0
#> 21.1 24.00 0 47 0 0
#> 64.1 24.00 0 43 0 0
#> 98.1 24.00 0 34 1 0
#> 80 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 27 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 148 24.00 0 61 1 0
#> 141.1 24.00 0 44 1 0
#> 33.1 24.00 0 53 0 0
#> 142 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 152 24.00 0 36 0 1
#> 20 24.00 0 46 1 0
#> 83 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 138.1 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 22.1 24.00 0 52 1 0
#> 118 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 152.1 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 71.1 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 126.2 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 98.2 24.00 0 34 1 0
#> 1 24.00 0 23 1 0
#> 191.1 24.00 0 60 0 1
#> 46.1 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 20.1 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 17.1 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 141.2 24.00 0 44 1 0
#> 141.3 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 172.1 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 38 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 98.3 24.00 0 34 1 0
#> 152.2 24.00 0 36 0 1
#> 104.2 24.00 0 50 1 0
#> 71.2 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 143.1 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 142.1 24.00 0 53 0 0
#> 71.3 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.36 NA NA NA
#> 2 age, Cure model 0.0248 NA NA NA
#> 3 grade_ii, Cure model 0.143 NA NA NA
#> 4 grade_iii, Cure model 1.17 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0155 NA NA NA
#> 2 grade_ii, Survival model 0.624 NA NA NA
#> 3 grade_iii, Survival model 0.403 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.36492 0.02484 0.14281 1.16537
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 245.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.36491695 0.02484497 0.14280906 1.16536534
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01553253 0.62362335 0.40264514
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0197631462 0.9309588862 0.3251557127 0.5341997433 0.1914969812
#> [6] 0.1148979918 0.6423265773 0.0716905798 0.0324265816 0.1433484373
#> [11] 0.4993365185 0.4648981754 0.3356278311 0.0148526834 0.7708547343
#> [16] 0.8232754487 0.0655869242 0.1148979918 0.7322705379 0.9723127638
#> [21] 0.0426120715 0.7322705379 0.7063840446 0.7322705379 0.8762237514
#> [26] 0.6677205475 0.2645503342 0.1015178483 0.6423265773 0.5341997433
#> [31] 0.0373500754 0.2548688893 0.0008434730 0.3986292578 0.0072339704
#> [36] 0.0008434730 0.4312672455 0.0481203140 0.3666635199 0.8762237514
#> [41] 0.9034532463 0.1148979918 0.5806868960 0.2358721989 0.1747964862
#> [46] 0.2843977166 0.5806868960 0.1747964862 0.0008434730 0.3986292578
#> [51] 0.2358721989 0.3356278311 0.3666635199 0.3356278311 0.7840308286
#> [56] 0.0197631462 0.8232754487 0.6172826432 0.4993365185 0.6934246189
#> [61] 0.6172826432 0.0001199881 0.0278900352 0.1586990651 0.0777686191
#> [66] 0.7840308286 0.5341997433 0.4877258760 0.7840308286 0.5341997433
#> [71] 0.1586990651 0.0072339704 0.9861661190 0.2743923703 0.1080824209
#> [76] 0.3147267599 0.2944035216 0.1914969812 0.9447571997 0.1914969812
#> [81] 0.0777686191 0.8232754487 0.4648981754 0.0777686191 0.2177346419
#> [86] 0.7192566929 0.2177346419 0.6805322599 0.4993365185 0.3666635199
#> [91] 0.0951224638 0.1433484373 0.1358330894 0.4423892211 0.0008434730
#> [96] 0.3986292578 0.4535960813 0.8232754487 0.3045052040 0.9034532463
#> [101] 0.6049285652 0.0596557547 0.9585518874 0.0538241479 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 63 101 106 18 88 55 13 32 66 97 29 6 171
#> 22.77 9.97 16.67 15.21 18.37 19.34 14.34 20.90 22.13 19.14 15.45 15.64 16.57
#> 92 43 159 90 58 49 77 197 49.1 154 49.2 10 60
#> 22.92 12.10 10.55 20.94 19.34 12.19 7.27 21.60 12.19 12.63 12.19 10.53 13.15
#> 184 158 13.1 18.1 175 41 168 181 164 168.1 192 139 130
#> 17.77 20.14 14.34 15.21 21.91 18.02 23.72 16.46 23.60 23.72 16.44 21.49 16.47
#> 10.1 52 55.1 157 51 8 117 157.1 8.1 168.2 181.1 51.1 171.1
#> 10.53 10.42 19.34 15.10 18.23 18.43 17.46 15.10 18.43 23.72 16.46 18.23 16.57
#> 130.1 171.2 107 63.1 159.1 133 29.1 14 133.1 78 194 179 128
#> 16.47 16.57 11.18 22.77 10.55 14.65 15.45 12.89 14.65 23.88 22.40 18.63 20.35
#> 107.1 18.2 167 107.2 18.3 179.1 164.1 25 110 105 23 111 88.1
#> 11.18 15.21 15.55 11.18 15.21 18.63 23.60 6.32 17.56 19.75 16.92 17.45 18.37
#> 187 88.2 128.1 159.2 6.1 128.2 108 56 108.1 155 29.2 130.2 150
#> 9.92 18.37 20.35 10.55 15.64 20.35 18.29 12.21 18.29 13.08 15.45 16.47 20.33
#> 97.1 76 26 168.3 181.2 125 159.3 45 52.1 180 99 70 153
#> 19.14 19.22 15.77 23.72 16.46 15.65 10.55 17.42 10.42 14.82 21.19 7.38 21.33
#> 64 126 34 162 21 71 191 98 156 44 173 33 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 98.1 80 22 160 138 84 27 163 120 186 143 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 141 116 148 141.1 33.1 142 34.1 152 20 83 48 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 80.1 165 46 172 22.1 118 35.1 152.1 178 71.1 126.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.2 74 17 98.2 1 191.1 46.1 161 75 20.1 75.1 62 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 104 104.1 141.2 141.3 67 172.1 9 72 38 48.1 98.3 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.2 71.2 144 143.1 53 142.1 71.3 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[43]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004252812 0.445050707 -0.152410331
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.070919740 -0.002466882 0.006909987
#> grade_iii, Cure model
#> 1.145854665
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 26 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 57 14.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 55 19.34 1 69 0 1
#> 49 12.19 1 48 1 0
#> 41 18.02 1 40 1 0
#> 184 17.77 1 38 0 0
#> 42 12.43 1 49 0 1
#> 101 9.97 1 10 0 1
#> 60 13.15 1 38 1 0
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 183 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 56 12.21 1 60 0 0
#> 25 6.32 1 34 1 0
#> 6 15.64 1 39 0 0
#> 58 19.34 1 39 0 0
#> 107 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 125 15.65 1 67 1 0
#> 194 22.40 1 38 0 1
#> 81 14.06 1 34 0 0
#> 111 17.45 1 47 0 1
#> 150.1 20.33 1 48 0 0
#> 37 12.52 1 57 1 0
#> 106 16.67 1 49 1 0
#> 36 21.19 1 48 0 1
#> 181 16.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 171 16.57 1 41 0 1
#> 68 20.62 1 44 0 0
#> 79 16.23 1 54 1 0
#> 5 16.43 1 51 0 1
#> 37.1 12.52 1 57 1 0
#> 101.1 9.97 1 10 0 1
#> 23.1 16.92 1 61 0 0
#> 76 19.22 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 52 10.42 1 52 0 1
#> 170 19.54 1 43 0 1
#> 10.1 10.53 1 34 0 0
#> 149 8.37 1 33 1 0
#> 188 16.16 1 46 0 1
#> 69.1 23.23 1 25 0 1
#> 25.1 6.32 1 34 1 0
#> 188.1 16.16 1 46 0 1
#> 90 20.94 1 50 0 1
#> 49.1 12.19 1 48 1 0
#> 70 7.38 1 30 1 0
#> 18 15.21 1 49 1 0
#> 181.1 16.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 93 10.33 1 52 0 1
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 69.2 23.23 1 25 0 1
#> 51 18.23 1 83 0 1
#> 85 16.44 1 36 0 0
#> 52.1 10.42 1 52 0 1
#> 139 21.49 1 63 1 0
#> 164 23.60 1 76 0 1
#> 90.1 20.94 1 50 0 1
#> 13 14.34 1 54 0 1
#> 136 21.83 1 43 0 1
#> 30 17.43 1 78 0 0
#> 155 13.08 1 26 0 0
#> 5.1 16.43 1 51 0 1
#> 56.1 12.21 1 60 0 0
#> 136.1 21.83 1 43 0 1
#> 23.2 16.92 1 61 0 0
#> 25.2 6.32 1 34 1 0
#> 96 14.54 1 33 0 1
#> 5.2 16.43 1 51 0 1
#> 134 17.81 1 47 1 0
#> 170.1 19.54 1 43 0 1
#> 86 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 181.2 16.46 1 45 0 1
#> 42.1 12.43 1 49 0 1
#> 105 19.75 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 101.2 9.97 1 10 0 1
#> 153 21.33 1 55 1 0
#> 187.1 9.92 1 39 1 0
#> 128 20.35 1 35 0 1
#> 105.1 19.75 1 60 0 0
#> 59.1 10.16 1 NA 1 0
#> 188.2 16.16 1 46 0 1
#> 81.1 14.06 1 34 0 0
#> 93.1 10.33 1 52 0 1
#> 92 22.92 1 47 0 1
#> 93.2 10.33 1 52 0 1
#> 159 10.55 1 50 0 1
#> 149.1 8.37 1 33 1 0
#> 32 20.90 1 37 1 0
#> 101.3 9.97 1 10 0 1
#> 51.1 18.23 1 83 0 1
#> 36.1 21.19 1 48 0 1
#> 177 12.53 1 75 0 0
#> 61 10.12 1 36 0 1
#> 157.1 15.10 1 47 0 0
#> 130 16.47 1 53 0 1
#> 130.1 16.47 1 53 0 1
#> 90.2 20.94 1 50 0 1
#> 52.2 10.42 1 52 0 1
#> 68.1 20.62 1 44 0 0
#> 80 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 94 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 112 24.00 0 61 0 0
#> 9 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 178 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 62 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 20 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 94.1 24.00 0 51 0 1
#> 27 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 12 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 148 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 104 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 112.1 24.00 0 61 0 0
#> 95 24.00 0 68 0 1
#> 132.1 24.00 0 55 0 0
#> 121 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 132.2 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 148.1 24.00 0 61 1 0
#> 186 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 62.1 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 198 24.00 0 66 0 1
#> 126 24.00 0 48 0 0
#> 38.1 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 116.1 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 62.2 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 7.1 24.00 0 37 1 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 144.1 24.00 0 28 0 1
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 28 24.00 0 67 1 0
#> 54.1 24.00 0 53 1 0
#> 144.2 24.00 0 28 0 1
#> 178.1 24.00 0 52 1 0
#> 38.2 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 47.1 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 46.1 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 53.1 24.00 0 32 0 1
#> 95.1 24.00 0 68 0 1
#> 131.1 24.00 0 66 0 0
#> 46.2 24.00 0 71 0 0
#> 165.1 24.00 0 47 0 0
#> 131.2 24.00 0 66 0 0
#> 87.1 24.00 0 27 0 0
#> 109 24.00 0 48 0 0
#> 119.1 24.00 0 17 0 0
#> 162 24.00 0 51 0 0
#> 131.3 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 27.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0709 NA NA NA
#> 2 age, Cure model -0.00247 NA NA NA
#> 3 grade_ii, Cure model 0.00691 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00425 NA NA NA
#> 2 grade_ii, Survival model 0.445 NA NA NA
#> 3 grade_iii, Survival model -0.152 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.070920 -0.002467 0.006910 1.145855
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 267.6
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.070919740 -0.002466882 0.006909987 1.145854665
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004252812 0.445050707 -0.152410331
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.553270798 0.512888948 0.173741094 0.583520326 0.768633740 0.737510489
#> [7] 0.215424651 0.716987556 0.268637614 0.295663253 0.675756717 0.862945889
#> [13] 0.624507442 0.277747856 0.331770678 0.926669905 0.157723560 0.696303389
#> [19] 0.969013376 0.533092576 0.215424651 0.747893466 0.082800385 0.523007698
#> [25] 0.047292048 0.604026709 0.304622439 0.157723560 0.655397570 0.359071860
#> [31] 0.082800385 0.396433324 0.905367347 0.368348738 0.134168353 0.463541725
#> [37] 0.434492333 0.655397570 0.862945889 0.331770678 0.232677102 0.016995385
#> [43] 0.789351835 0.198519691 0.768633740 0.937361650 0.473384005 0.016995385
#> [49] 0.969013376 0.473384005 0.103870500 0.716987556 0.958452796 0.543206701
#> [55] 0.396433324 0.241576261 0.820605294 0.040560167 0.001643436 0.016995385
#> [61] 0.250535243 0.424790187 0.789351835 0.068375119 0.010616646 0.103870500
#> [67] 0.593745404 0.054293814 0.322586667 0.634777533 0.434492333 0.696303389
#> [73] 0.054293814 0.331770678 0.969013376 0.573347112 0.434492333 0.286744413
#> [79] 0.198519691 0.005459999 0.502830307 0.396433324 0.675756717 0.182015672
#> [85] 0.304622439 0.862945889 0.075668232 0.905367347 0.149656443 0.182015672
#> [91] 0.473384005 0.604026709 0.820605294 0.033394908 0.820605294 0.758241914
#> [97] 0.937361650 0.126346711 0.862945889 0.250535243 0.082800385 0.645065049
#> [103] 0.852234356 0.553270798 0.377691214 0.377691214 0.103870500 0.789351835
#> [109] 0.134168353 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 157 26 166 57 10 43 55 49 41 184 42 101 60
#> 15.10 15.77 19.98 14.46 10.53 12.10 19.34 12.19 18.02 17.77 12.43 9.97 13.15
#> 40 23 183 150 56 25 6 58 107 99 125 194 81
#> 18.00 16.92 9.24 20.33 12.21 6.32 15.64 19.34 11.18 21.19 15.65 22.40 14.06
#> 111 150.1 37 106 36 181 187 171 68 79 5 37.1 101.1
#> 17.45 20.33 12.52 16.67 21.19 16.46 9.92 16.57 20.62 16.23 16.43 12.52 9.97
#> 23.1 76 69 52 170 10.1 149 188 69.1 25.1 188.1 90 49.1
#> 16.92 19.22 23.23 10.42 19.54 10.53 8.37 16.16 23.23 6.32 16.16 20.94 12.19
#> 70 18 181.1 88 93 63 78 69.2 51 85 52.1 139 164
#> 7.38 15.21 16.46 18.37 10.33 22.77 23.88 23.23 18.23 16.44 10.42 21.49 23.60
#> 90.1 13 136 30 155 5.1 56.1 136.1 23.2 25.2 96 5.2 134
#> 20.94 14.34 21.83 17.43 13.08 16.43 12.21 21.83 16.92 6.32 14.54 16.43 17.81
#> 170.1 86 100 181.2 42.1 105 111.1 101.2 153 187.1 128 105.1 188.2
#> 19.54 23.81 16.07 16.46 12.43 19.75 17.45 9.97 21.33 9.92 20.35 19.75 16.16
#> 81.1 93.1 92 93.2 159 149.1 32 101.3 51.1 36.1 177 61 157.1
#> 14.06 10.33 22.92 10.33 10.55 8.37 20.90 9.97 18.23 21.19 12.53 10.12 15.10
#> 130 130.1 90.2 52.2 68.1 80 87 94 173 112 9 9.1 135
#> 16.47 16.47 20.94 10.42 20.62 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 74 62 119 20 22 2 94.1 27 152 31 132 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 54 12 48 35 137 116 148 82 104 165 112.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 121 47 132.2 38 3 44 148.1 186 7 98 174 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 1 198 126 38.1 67 116.1 120 62.2 11 7.1 141 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 46 28 54.1 144.2 178.1 38.2 137.1 47.1 142 17 46.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 95.1 131.1 46.2 165.1 131.2 87.1 109 119.1 162 131.3 109.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[44]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004997254 0.252611153 0.086505005
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.1964494 0.0273670 -0.4755007
#> grade_iii, Cure model
#> 0.8487443
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 108 18.29 1 39 0 1
#> 42 12.43 1 49 0 1
#> 92 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 153 21.33 1 55 1 0
#> 195 11.76 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 129 23.41 1 53 1 0
#> 66 22.13 1 53 0 0
#> 30 17.43 1 78 0 0
#> 8 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 99 21.19 1 38 0 1
#> 190 20.81 1 42 1 0
#> 37 12.52 1 57 1 0
#> 187 9.92 1 39 1 0
#> 30.1 17.43 1 78 0 0
#> 158 20.14 1 74 1 0
#> 99.1 21.19 1 38 0 1
#> 29 15.45 1 68 1 0
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 108.1 18.29 1 39 0 1
#> 129.1 23.41 1 53 1 0
#> 81 14.06 1 34 0 0
#> 177 12.53 1 75 0 0
#> 79 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 106.1 16.67 1 49 1 0
#> 26 15.77 1 49 0 1
#> 117 17.46 1 26 0 1
#> 128 20.35 1 35 0 1
#> 42.1 12.43 1 49 0 1
#> 41 18.02 1 40 1 0
#> 184 17.77 1 38 0 0
#> 108.2 18.29 1 39 0 1
#> 81.1 14.06 1 34 0 0
#> 16 8.71 1 71 0 1
#> 179 18.63 1 42 0 0
#> 177.1 12.53 1 75 0 0
#> 145 10.07 1 65 1 0
#> 29.1 15.45 1 68 1 0
#> 69 23.23 1 25 0 1
#> 145.1 10.07 1 65 1 0
#> 10 10.53 1 34 0 0
#> 99.2 21.19 1 38 0 1
#> 68 20.62 1 44 0 0
#> 155 13.08 1 26 0 0
#> 197 21.60 1 69 1 0
#> 169.1 22.41 1 46 0 0
#> 133.1 14.65 1 57 0 0
#> 26.1 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 157 15.10 1 47 0 0
#> 78.1 23.88 1 43 0 0
#> 69.1 23.23 1 25 0 1
#> 100 16.07 1 60 0 0
#> 153.1 21.33 1 55 1 0
#> 14 12.89 1 21 0 0
#> 76 19.22 1 54 0 1
#> 194 22.40 1 38 0 1
#> 66.1 22.13 1 53 0 0
#> 13 14.34 1 54 0 1
#> 15 22.68 1 48 0 0
#> 128.1 20.35 1 35 0 1
#> 181 16.46 1 45 0 1
#> 30.2 17.43 1 78 0 0
#> 153.2 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 149 8.37 1 33 1 0
#> 170 19.54 1 43 0 1
#> 145.2 10.07 1 65 1 0
#> 52 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 8.1 18.43 1 32 0 0
#> 125 15.65 1 67 1 0
#> 39 15.59 1 37 0 1
#> 189 10.51 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 40 18.00 1 28 1 0
#> 5 16.43 1 51 0 1
#> 37.1 12.52 1 57 1 0
#> 14.1 12.89 1 21 0 0
#> 26.2 15.77 1 49 0 1
#> 77 7.27 1 67 0 1
#> 171 16.57 1 41 0 1
#> 70 7.38 1 30 1 0
#> 55 19.34 1 69 0 1
#> 36 21.19 1 48 0 1
#> 81.2 14.06 1 34 0 0
#> 93 10.33 1 52 0 1
#> 16.1 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 195.1 11.76 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 91 5.33 1 61 0 1
#> 124 9.73 1 NA 1 0
#> 69.2 23.23 1 25 0 1
#> 188 16.16 1 46 0 1
#> 124.1 9.73 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 15.1 22.68 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 189.1 10.51 1 NA 1 0
#> 133.2 14.65 1 57 0 0
#> 90 20.94 1 50 0 1
#> 77.1 7.27 1 67 0 1
#> 183 9.24 1 67 1 0
#> 164 23.60 1 76 0 1
#> 150.1 20.33 1 48 0 0
#> 164.1 23.60 1 76 0 1
#> 147 24.00 0 76 1 0
#> 186 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 87 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 9.1 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 182 24.00 0 35 0 0
#> 165.1 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 193.1 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 137 24.00 0 45 1 0
#> 27.1 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 119 24.00 0 17 0 0
#> 53 24.00 0 32 0 1
#> 28 24.00 0 67 1 0
#> 104 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 82 24.00 0 34 0 0
#> 191 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 11 24.00 0 42 0 1
#> 11.1 24.00 0 42 0 1
#> 64 24.00 0 43 0 0
#> 119.1 24.00 0 17 0 0
#> 103 24.00 0 56 1 0
#> 126 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 118 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 185 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 9.2 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 1 24.00 0 23 1 0
#> 1.1 24.00 0 23 1 0
#> 98 24.00 0 34 1 0
#> 80.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 137.1 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 3 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 1.2 24.00 0 23 1 0
#> 20 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 131 24.00 0 66 0 0
#> 9.3 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 72.2 24.00 0 40 0 1
#> 54.1 24.00 0 53 1 0
#> 147.1 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 72.3 24.00 0 40 0 1
#> 120.1 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 44 24.00 0 56 0 0
#> 165.2 24.00 0 47 0 0
#> 80.2 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 122 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 82.1 24.00 0 34 0 0
#> 54.2 24.00 0 53 1 0
#> 33 24.00 0 53 0 0
#> 54.3 24.00 0 53 1 0
#> 143 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.20 NA NA NA
#> 2 age, Cure model 0.0274 NA NA NA
#> 3 grade_ii, Cure model -0.476 NA NA NA
#> 4 grade_iii, Cure model 0.849 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00500 NA NA NA
#> 2 grade_ii, Survival model 0.253 NA NA NA
#> 3 grade_iii, Survival model 0.0865 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.19645 0.02737 -0.47550 0.84874
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 249.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1964494 0.0273670 -0.4755007 0.8487443
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004997254 0.252611153 0.086505005
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.54853473 0.87781254 0.18245191 0.63946227 0.32669864 0.47830548
#> [7] 0.11548731 0.27023637 0.60717258 0.53138239 0.51395736 0.35651608
#> [13] 0.40403442 0.86373332 0.94000823 0.60717258 0.46010518 0.35651608
#> [19] 0.74782746 0.76998170 0.03622104 0.54853473 0.11548731 0.79904850
#> [25] 0.84948889 0.68683305 0.23389817 0.63946227 0.71009659 0.59884772
#> [31] 0.42313828 0.87781254 0.57368104 0.59049480 0.54853473 0.79904850
#> [37] 0.95355533 0.52268683 0.84948889 0.91969415 0.74782746 0.14414407
#> [43] 0.91969415 0.89880038 0.35651608 0.41361347 0.82062791 0.30511698
#> [49] 0.23389817 0.76998170 0.71009659 0.46922925 0.76258561 0.03622104
#> [55] 0.14414407 0.70237273 0.32669864 0.82787615 0.50515179 0.25804982
#> [61] 0.27023637 0.79175281 0.20908737 0.42313828 0.66330511 0.60717258
#> [67] 0.32669864 0.63133914 0.96691126 0.48732189 0.91969415 0.90578710
#> [73] 0.29344126 0.53138239 0.73273012 0.74029079 0.44172649 0.89180359
#> [79] 0.58211710 0.67122860 0.86373332 0.82787615 0.71009659 0.98024306
#> [85] 0.65534690 0.97358847 0.49628002 0.35651608 0.79904850 0.91275159
#> [91] 0.95355533 0.84228137 0.19585328 0.99341369 0.14414407 0.69461906
#> [97] 0.67122860 0.20908737 0.30511698 0.76998170 0.39431995 0.98024306
#> [103] 0.94680115 0.08114819 0.44172649 0.08114819 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 108 42 92 106 153 105 129 66 30 8 97 99 190
#> 18.29 12.43 22.92 16.67 21.33 19.75 23.41 22.13 17.43 18.43 19.14 21.19 20.81
#> 37 187 30.1 158 99.1 29 133 78 108.1 129.1 81 177 79
#> 12.52 9.92 17.43 20.14 21.19 15.45 14.65 23.88 18.29 23.41 14.06 12.53 16.23
#> 169 106.1 26 117 128 42.1 41 184 108.2 81.1 16 179 177.1
#> 22.41 16.67 15.77 17.46 20.35 12.43 18.02 17.77 18.29 14.06 8.71 18.63 12.53
#> 145 29.1 69 145.1 10 99.2 68 155 197 169.1 133.1 26.1 166
#> 10.07 15.45 23.23 10.07 10.53 21.19 20.62 13.08 21.60 22.41 14.65 15.77 19.98
#> 157 78.1 69.1 100 153.1 14 76 194 66.1 13 15 128.1 181
#> 15.10 23.88 23.23 16.07 21.33 12.89 19.22 22.40 22.13 14.34 22.68 20.35 16.46
#> 30.2 153.2 23 149 170 145.2 52 136 8.1 125 39 150 43
#> 17.43 21.33 16.92 8.37 19.54 10.07 10.42 21.83 18.43 15.65 15.59 20.33 12.10
#> 40 5 37.1 14.1 26.2 77 171 70 55 36 81.2 93 16.1
#> 18.00 16.43 12.52 12.89 15.77 7.27 16.57 7.38 19.34 21.19 14.06 10.33 8.71
#> 154 113 91 69.2 188 5.1 15.1 197.1 133.2 90 77.1 183 164
#> 12.63 22.86 5.33 23.23 16.16 16.43 22.68 21.60 14.65 20.94 7.27 9.24 23.60
#> 150.1 164.1 147 186 65 9 151 31 87 2 9.1 65.1 165
#> 20.33 23.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 2.1 172 27 193 182 165.1 161 193.1 141 146 80 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 27.1 72 119 53 28 104 83 82 191 120 11 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 119.1 103 126 135 142 152 118 67 185 118.1 35 9.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 1 1.1 98 80.1 17 116 137.1 132 3 71.1 1.2 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 7 131 9.3 54 102 72.2 54.1 147.1 176 109 72.3 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 44 165.2 80.2 12 122 156 82.1 54.2 33 54.3 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[45]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003685423 0.611282573 0.071846945
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.36318238 0.01024015 -0.06316658
#> grade_iii, Cure model
#> 0.26597915
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 70 7.38 1 30 1 0
#> 106 16.67 1 49 1 0
#> 199 19.81 1 NA 0 1
#> 58 19.34 1 39 0 0
#> 43 12.10 1 61 0 1
#> 10 10.53 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 63 22.77 1 31 1 0
#> 100 16.07 1 60 0 0
#> 15 22.68 1 48 0 0
#> 58.1 19.34 1 39 0 0
#> 192 16.44 1 31 1 0
#> 76 19.22 1 54 0 1
#> 26 15.77 1 49 0 1
#> 159 10.55 1 50 0 1
#> 57 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 70.1 7.38 1 30 1 0
#> 10.2 10.53 1 34 0 0
#> 70.2 7.38 1 30 1 0
#> 100.1 16.07 1 60 0 0
#> 158 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 79 16.23 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 90 20.94 1 50 0 1
#> 107 11.18 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 154 12.63 1 20 1 0
#> 32 20.90 1 37 1 0
#> 63.1 22.77 1 31 1 0
#> 52 10.42 1 52 0 1
#> 10.3 10.53 1 34 0 0
#> 158.1 20.14 1 74 1 0
#> 153 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 110.1 17.56 1 65 0 1
#> 166 19.98 1 48 0 0
#> 188 16.16 1 46 0 1
#> 92 22.92 1 47 0 1
#> 155 13.08 1 26 0 0
#> 183 9.24 1 67 1 0
#> 4 17.64 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 41 18.02 1 40 1 0
#> 136 21.83 1 43 0 1
#> 183.1 9.24 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 68 20.62 1 44 0 0
#> 69 23.23 1 25 0 1
#> 194.1 22.40 1 38 0 1
#> 66 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 113.1 22.86 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 23 16.92 1 61 0 0
#> 70.3 7.38 1 30 1 0
#> 5 16.43 1 51 0 1
#> 188.1 16.16 1 46 0 1
#> 175 21.91 1 43 0 0
#> 88 18.37 1 47 0 0
#> 108.1 18.29 1 39 0 1
#> 175.1 21.91 1 43 0 0
#> 183.2 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 55 19.34 1 69 0 1
#> 127 3.53 1 62 0 1
#> 166.1 19.98 1 48 0 0
#> 86 23.81 1 58 0 1
#> 25.1 6.32 1 34 1 0
#> 175.2 21.91 1 43 0 0
#> 130 16.47 1 53 0 1
#> 175.3 21.91 1 43 0 0
#> 96 14.54 1 33 0 1
#> 60 13.15 1 38 1 0
#> 68.1 20.62 1 44 0 0
#> 60.1 13.15 1 38 1 0
#> 57.1 14.46 1 45 0 1
#> 171 16.57 1 41 0 1
#> 100.2 16.07 1 60 0 0
#> 114.1 13.68 1 NA 0 0
#> 43.1 12.10 1 61 0 1
#> 61 10.12 1 36 0 1
#> 188.2 16.16 1 46 0 1
#> 106.1 16.67 1 49 1 0
#> 124 9.73 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 6 15.64 1 39 0 0
#> 127.1 3.53 1 62 0 1
#> 97 19.14 1 65 0 1
#> 169 22.41 1 46 0 0
#> 45 17.42 1 54 0 1
#> 170 19.54 1 43 0 1
#> 90.1 20.94 1 50 0 1
#> 41.1 18.02 1 40 1 0
#> 86.1 23.81 1 58 0 1
#> 56 12.21 1 60 0 0
#> 194.2 22.40 1 38 0 1
#> 154.1 12.63 1 20 1 0
#> 123.1 13.00 1 44 1 0
#> 171.1 16.57 1 41 0 1
#> 133 14.65 1 57 0 0
#> 190 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 149 8.37 1 33 1 0
#> 15.1 22.68 1 48 0 0
#> 132 24.00 0 55 0 0
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 72 24.00 0 40 0 1
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 146 24.00 0 63 1 0
#> 27 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 142 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 103 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 121 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 176 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 200 24.00 0 64 0 0
#> 19 24.00 0 57 0 1
#> 95.1 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 118.1 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 118.2 24.00 0 44 1 0
#> 176.1 24.00 0 43 0 1
#> 144.1 24.00 0 28 0 1
#> 193 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 104 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 148.1 24.00 0 61 1 0
#> 115 24.00 0 NA 1 0
#> 186.1 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 173.1 24.00 0 19 0 1
#> 146.1 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 98 24.00 0 34 1 0
#> 95.2 24.00 0 68 0 1
#> 19.1 24.00 0 57 0 1
#> 196.1 24.00 0 19 0 0
#> 95.3 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 144.2 24.00 0 28 0 1
#> 2 24.00 0 9 0 0
#> 178 24.00 0 52 1 0
#> 142.1 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 116.1 24.00 0 58 0 1
#> 1.1 24.00 0 23 1 0
#> 173.2 24.00 0 19 0 1
#> 48.1 24.00 0 31 1 0
#> 186.2 24.00 0 45 1 0
#> 152.1 24.00 0 36 0 1
#> 3.1 24.00 0 31 1 0
#> 104.1 24.00 0 50 1 0
#> 95.4 24.00 0 68 0 1
#> 112.1 24.00 0 61 0 0
#> 2.1 24.00 0 9 0 0
#> 2.2 24.00 0 9 0 0
#> 182.1 24.00 0 35 0 0
#> 35.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 142.2 24.00 0 53 0 0
#> 112.2 24.00 0 61 0 0
#> 34 24.00 0 36 0 0
#> 147 24.00 0 76 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.363 NA NA NA
#> 2 age, Cure model 0.0102 NA NA NA
#> 3 grade_ii, Cure model -0.0632 NA NA NA
#> 4 grade_iii, Cure model 0.266 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00369 NA NA NA
#> 2 grade_ii, Survival model 0.611 NA NA NA
#> 3 grade_iii, Survival model 0.0718 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.36318 0.01024 -0.06317 0.26598
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 258 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.36318238 0.01024015 -0.06316658 0.26597915
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003685423 0.611282573 0.071846945
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.21887303 0.94287291 0.62518661 0.47428460 0.83974127 0.86792689
#> [7] 0.86792689 0.14910903 0.71275467 0.17739065 0.47428460 0.66577904
#> [13] 0.50180170 0.73568863 0.86091475 0.76640751 0.59127486 0.94287291
#> [19] 0.86792689 0.94287291 0.71275467 0.42689086 0.55642028 0.68177019
#> [25] 0.41660780 0.35302607 0.85388589 0.81834020 0.37496393 0.14910903
#> [31] 0.89551985 0.86792689 0.42689086 0.34167221 0.97480398 0.59127486
#> [37] 0.44592284 0.68963671 0.09354062 0.79639130 0.91632527 0.11372942
#> [43] 0.53842979 0.57414776 0.31735871 0.91632527 0.50180170 0.55642028
#> [49] 0.39618481 0.07209126 0.21887303 0.25675047 0.90943378 0.11372942
#> [55] 0.80383461 0.61671934 0.94287291 0.67378869 0.68963671 0.26990680
#> [61] 0.52928402 0.53842979 0.26990680 0.91632527 0.32982356 0.47428460
#> [67] 0.98743014 0.44592284 0.03400035 0.97480398 0.26990680 0.65766536
#> [73] 0.26990680 0.75875244 0.78156040 0.39618481 0.78156040 0.76640751
#> [79] 0.64147731 0.71275467 0.83974127 0.90248290 0.68963671 0.62518661
#> [85] 0.74339089 0.98743014 0.52010826 0.20483637 0.60822266 0.46479906
#> [91] 0.35302607 0.57414776 0.03400035 0.83259720 0.21887303 0.81834020
#> [97] 0.80383461 0.64147731 0.75108085 0.38574232 0.96837942 0.93623870
#> [103] 0.17739065 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 194 70 106 58 43 10 10.1 63 100 15 58.1 192 76
#> 22.40 7.38 16.67 19.34 12.10 10.53 10.53 22.77 16.07 22.68 19.34 16.44 19.22
#> 26 159 57 110 70.1 10.2 70.2 100.1 158 51 79 128 90
#> 15.77 10.55 14.46 17.56 7.38 10.53 7.38 16.07 20.14 18.23 16.23 20.35 20.94
#> 107 154 32 63.1 52 10.3 158.1 153 25 110.1 166 188 92
#> 11.18 12.63 20.90 22.77 10.42 10.53 20.14 21.33 6.32 17.56 19.98 16.16 22.92
#> 155 183 113 108 41 136 183.1 76.1 51.1 68 69 194.1 66
#> 13.08 9.24 22.86 18.29 18.02 21.83 9.24 19.22 18.23 20.62 23.23 22.40 22.13
#> 187 113.1 123 23 70.3 5 188.1 175 88 108.1 175.1 183.2 197
#> 9.92 22.86 13.00 16.92 7.38 16.43 16.16 21.91 18.37 18.29 21.91 9.24 21.60
#> 55 127 166.1 86 25.1 175.2 130 175.3 96 60 68.1 60.1 57.1
#> 19.34 3.53 19.98 23.81 6.32 21.91 16.47 21.91 14.54 13.15 20.62 13.15 14.46
#> 171 100.2 43.1 61 188.2 106.1 6 127.1 97 169 45 170 90.1
#> 16.57 16.07 12.10 10.12 16.16 16.67 15.64 3.53 19.14 22.41 17.42 19.54 20.94
#> 41.1 86.1 56 194.2 154.1 123.1 171.1 133 190 77 149 15.1 132
#> 18.02 23.81 12.21 22.40 12.63 13.00 16.57 14.65 20.81 7.27 8.37 22.68 24.00
#> 83 11 87 72 191 186 146 27 165 48 9 148 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 62 28 151 103 95 144 173 121 64 176 75 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 95.1 118 152 118.1 156 35 74 3 47 116 120 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.2 176.1 144.1 193 196 104 182 148.1 186.1 1 173.1 146.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 98 95.2 19.1 196.1 95.3 144.2 2 178 142.1 138 143 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 1.1 173.2 48.1 186.2 152.1 3.1 104.1 95.4 112.1 2.1 2.2 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 120.1 141 142.2 112.2 34 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[46]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01774217 0.46746607 0.48875405
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.115994805 -0.002059818 0.082356665
#> grade_iii, Cure model
#> 1.208439391
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 16 8.71 1 71 0 1
#> 164 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 51 18.23 1 83 0 1
#> 110 17.56 1 65 0 1
#> 25 6.32 1 34 1 0
#> 32 20.90 1 37 1 0
#> 56 12.21 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 15 22.68 1 48 0 0
#> 117 17.46 1 26 0 1
#> 139 21.49 1 63 1 0
#> 40 18.00 1 28 1 0
#> 92 22.92 1 47 0 1
#> 187 9.92 1 39 1 0
#> 70 7.38 1 30 1 0
#> 50 10.02 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 113 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 52 10.42 1 52 0 1
#> 111.1 17.45 1 47 0 1
#> 16.1 8.71 1 71 0 1
#> 55 19.34 1 69 0 1
#> 128.1 20.35 1 35 0 1
#> 50.1 10.02 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 139.1 21.49 1 63 1 0
#> 164.1 23.60 1 76 0 1
#> 195 11.76 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 5 16.43 1 51 0 1
#> 188 16.16 1 46 0 1
#> 153 21.33 1 55 1 0
#> 190 20.81 1 42 1 0
#> 50.2 10.02 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 123 13.00 1 44 1 0
#> 139.2 21.49 1 63 1 0
#> 26 15.77 1 49 0 1
#> 197 21.60 1 69 1 0
#> 14.1 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 97 19.14 1 65 0 1
#> 117.1 17.46 1 26 0 1
#> 50.3 10.02 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 49 12.19 1 48 1 0
#> 24.1 23.89 1 38 0 0
#> 106 16.67 1 49 1 0
#> 40.1 18.00 1 28 1 0
#> 129 23.41 1 53 1 0
#> 50.4 10.02 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 18 15.21 1 49 1 0
#> 114.1 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 25.1 6.32 1 34 1 0
#> 113.1 22.86 1 34 0 0
#> 170 19.54 1 43 0 1
#> 123.1 13.00 1 44 1 0
#> 39 15.59 1 37 0 1
#> 97.1 19.14 1 65 0 1
#> 113.2 22.86 1 34 0 0
#> 133.1 14.65 1 57 0 0
#> 10 10.53 1 34 0 0
#> 149 8.37 1 33 1 0
#> 129.1 23.41 1 53 1 0
#> 77 7.27 1 67 0 1
#> 194 22.40 1 38 0 1
#> 175 21.91 1 43 0 0
#> 79 16.23 1 54 1 0
#> 134 17.81 1 47 1 0
#> 14.2 12.89 1 21 0 0
#> 139.3 21.49 1 63 1 0
#> 77.1 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 16.2 8.71 1 71 0 1
#> 26.1 15.77 1 49 0 1
#> 5.1 16.43 1 51 0 1
#> 49.1 12.19 1 48 1 0
#> 199.1 19.81 1 NA 0 1
#> 134.1 17.81 1 47 1 0
#> 106.2 16.67 1 49 1 0
#> 37 12.52 1 57 1 0
#> 169 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 41 18.02 1 40 1 0
#> 89 11.44 1 NA 0 0
#> 155.1 13.08 1 26 0 0
#> 190.1 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 171 16.57 1 41 0 1
#> 88.1 18.37 1 47 0 0
#> 50.5 10.02 1 NA 1 0
#> 106.3 16.67 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 88.2 18.37 1 47 0 0
#> 86 23.81 1 58 0 1
#> 154.1 12.63 1 20 1 0
#> 39.1 15.59 1 37 0 1
#> 155.2 13.08 1 26 0 0
#> 89.1 11.44 1 NA 0 0
#> 16.3 8.71 1 71 0 1
#> 111.2 17.45 1 47 0 1
#> 134.2 17.81 1 47 1 0
#> 58 19.34 1 39 0 0
#> 50.6 10.02 1 NA 1 0
#> 129.2 23.41 1 53 1 0
#> 85 16.44 1 36 0 0
#> 138 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 144 24.00 0 28 0 1
#> 46 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 21 24.00 0 47 0 0
#> 103.1 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 193 24.00 0 45 0 1
#> 104 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 109 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 35 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 138.1 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 191 24.00 0 60 0 1
#> 138.2 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 74 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 132 24.00 0 55 0 0
#> 147.1 24.00 0 76 1 0
#> 84 24.00 0 39 0 1
#> 71 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 9.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 12.1 24.00 0 63 0 0
#> 54.1 24.00 0 53 1 0
#> 161 24.00 0 45 0 0
#> 131 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 65 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 9.2 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 54.2 24.00 0 53 1 0
#> 132.1 24.00 0 55 0 0
#> 48 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 182 24.00 0 35 0 0
#> 147.2 24.00 0 76 1 0
#> 98 24.00 0 34 1 0
#> 186 24.00 0 45 1 0
#> 27.1 24.00 0 63 1 0
#> 161.1 24.00 0 45 0 0
#> 65.2 24.00 0 57 1 0
#> 137.1 24.00 0 45 1 0
#> 87.1 24.00 0 27 0 0
#> 185.1 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 196 24.00 0 19 0 0
#> 116.1 24.00 0 58 0 1
#> 3.1 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 80.1 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 103.2 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 137.2 24.00 0 45 1 0
#> 65.3 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 104.1 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 87.2 24.00 0 27 0 0
#> 176 24.00 0 43 0 1
#> 9.3 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.116 NA NA NA
#> 2 age, Cure model -0.00206 NA NA NA
#> 3 grade_ii, Cure model 0.0824 NA NA NA
#> 4 grade_iii, Cure model 1.21 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0177 NA NA NA
#> 2 grade_ii, Survival model 0.467 NA NA NA
#> 3 grade_iii, Survival model 0.489 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.11599 -0.00206 0.08236 1.20844
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 242.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.115994805 -0.002059818 0.082356665 1.208439391
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01774217 0.46746607 0.48875405
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8457075414 0.0037416818 0.1233436294 0.2097608789 0.2807645645
#> [6] 0.9685267724 0.1002397560 0.7422125777 0.6441162660 0.0324635792
#> [11] 0.2915513956 0.0599799668 0.2301212913 0.0169656969 0.8307727562
#> [16] 0.9216416602 0.3447762414 0.0207004482 0.3126839338 0.8009109882
#> [21] 0.3126839338 0.8457075414 0.1471429588 0.1233436294 0.7135411586
#> [26] 0.0599799668 0.0037416818 0.1816253892 0.4248772933 0.4613063576
#> [31] 0.0852169082 0.1079524361 0.5499462750 0.6166581131 0.0599799668
#> [36] 0.4737397139 0.0538665803 0.6441162660 0.0002816001 0.1639439160
#> [41] 0.2915513956 0.5764094322 0.7567927668 0.0002816001 0.3560957176
#> [46] 0.2301212913 0.0084690703 0.3560957176 0.5369543444 0.0926281670
#> [51] 0.9685267724 0.0207004482 0.1389787242 0.6166581131 0.5114862912
#> [56] 0.1639439160 0.0207004482 0.5499462750 0.7860282006 0.9061168198
#> [61] 0.0084690703 0.9371829322 0.0426821021 0.0481008449 0.4489658776
#> [66] 0.2501797508 0.6441162660 0.0599799668 0.9371829322 0.6856798090
#> [71] 0.8457075414 0.4737397139 0.4248772933 0.7567927668 0.2501797508
#> [76] 0.3560957176 0.7278176421 0.0373780794 0.8158917653 0.2198903598
#> [81] 0.5764094322 0.1079524361 0.4986894409 0.4010689279 0.1816253892
#> [86] 0.3560957176 0.1816253892 0.0020041098 0.6856798090 0.5114862912
#> [91] 0.5764094322 0.8457075414 0.3126839338 0.2501797508 0.1471429588
#> [96] 0.0084690703 0.4128921047 0.0000000000 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 16 164 128 51 110 25 32 56 14 15 117 139 40
#> 8.71 23.60 20.35 18.23 17.56 6.32 20.90 12.21 12.89 22.68 17.46 21.49 18.00
#> 92 187 70 30 113 111 52 111.1 16.1 55 128.1 177 139.1
#> 22.92 9.92 7.38 17.43 22.86 17.45 10.42 17.45 8.71 19.34 20.35 12.53 21.49
#> 164.1 88 5 188 153 190 133 123 139.2 26 197 14.1 24
#> 23.60 18.37 16.43 16.16 21.33 20.81 14.65 13.00 21.49 15.77 21.60 12.89 23.89
#> 97 117.1 155 49 24.1 106 40.1 129 106.1 18 90 25.1 113.1
#> 19.14 17.46 13.08 12.19 23.89 16.67 18.00 23.41 16.67 15.21 20.94 6.32 22.86
#> 170 123.1 39 97.1 113.2 133.1 10 149 129.1 77 194 175 79
#> 19.54 13.00 15.59 19.14 22.86 14.65 10.53 8.37 23.41 7.27 22.40 21.91 16.23
#> 134 14.2 139.3 77.1 154 16.2 26.1 5.1 49.1 134.1 106.2 37 169
#> 17.81 12.89 21.49 7.27 12.63 8.71 15.77 16.43 12.19 17.81 16.67 12.52 22.41
#> 101 41 155.1 190.1 6 171 88.1 106.3 88.2 86 154.1 39.1 155.2
#> 9.97 18.02 13.08 20.81 15.64 16.57 18.37 16.67 18.37 23.81 12.63 15.59 13.08
#> 16.3 111.2 134.2 58 129.2 85 138 62 12 144 46 103 21
#> 8.71 17.45 17.81 19.34 23.41 16.44 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 172 67 137 7 27 122 9 87 193 104 147 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 54 35 160 185 138.1 200 191 138.2 74 72 132 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 71 148 141 121 9.1 80 64 12.1 54.1 161 131 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 173 3 151 65 1 9.2 65.1 54.2 132.1 48 144.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.2 98 186 27.1 161.1 65.2 137.1 87.1 185.1 2 196 116.1 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 80.1 112 103.2 162 72.1 137.2 65.3 122.1 104.1 142 87.2 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.3
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[47]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003176589 0.758942857 0.301012449
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 1.06422584 -0.01972777 -0.24558705
#> grade_iii, Cure model
#> 0.59023055
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 113 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 40 18.00 1 28 1 0
#> 106 16.67 1 49 1 0
#> 101 9.97 1 10 0 1
#> 192 16.44 1 31 1 0
#> 180 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 164 23.60 1 76 0 1
#> 36 21.19 1 48 0 1
#> 139 21.49 1 63 1 0
#> 89 11.44 1 NA 0 0
#> 79 16.23 1 54 1 0
#> 8 18.43 1 32 0 0
#> 107 11.18 1 54 1 0
#> 24 23.89 1 38 0 0
#> 106.1 16.67 1 49 1 0
#> 110 17.56 1 65 0 1
#> 81 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 52 10.42 1 52 0 1
#> 85 16.44 1 36 0 0
#> 164.1 23.60 1 76 0 1
#> 68 20.62 1 44 0 0
#> 77.1 7.27 1 67 0 1
#> 40.1 18.00 1 28 1 0
#> 13 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 153 21.33 1 55 1 0
#> 170 19.54 1 43 0 1
#> 136.1 21.83 1 43 0 1
#> 183 9.24 1 67 1 0
#> 25 6.32 1 34 1 0
#> 43 12.10 1 61 0 1
#> 157 15.10 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 8.1 18.43 1 32 0 0
#> 15 22.68 1 48 0 0
#> 25.1 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 39 15.59 1 37 0 1
#> 32 20.90 1 37 1 0
#> 26 15.77 1 49 0 1
#> 106.2 16.67 1 49 1 0
#> 108 18.29 1 39 0 1
#> 37 12.52 1 57 1 0
#> 170.1 19.54 1 43 0 1
#> 195 11.76 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 45 17.42 1 54 0 1
#> 96 14.54 1 33 0 1
#> 8.2 18.43 1 32 0 0
#> 29 15.45 1 68 1 0
#> 114 13.68 1 NA 0 0
#> 179 18.63 1 42 0 0
#> 37.1 12.52 1 57 1 0
#> 58 19.34 1 39 0 0
#> 40.2 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 179.1 18.63 1 42 0 0
#> 24.1 23.89 1 38 0 0
#> 199.1 19.81 1 NA 0 1
#> 113.1 22.86 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 60 13.15 1 38 1 0
#> 93.1 10.33 1 52 0 1
#> 183.1 9.24 1 67 1 0
#> 159.1 10.55 1 50 0 1
#> 106.3 16.67 1 49 1 0
#> 16 8.71 1 71 0 1
#> 26.1 15.77 1 49 0 1
#> 145 10.07 1 65 1 0
#> 69 23.23 1 25 0 1
#> 175 21.91 1 43 0 0
#> 86 23.81 1 58 0 1
#> 180.1 14.82 1 37 0 0
#> 79.1 16.23 1 54 1 0
#> 158 20.14 1 74 1 0
#> 111 17.45 1 47 0 1
#> 187.1 9.92 1 39 1 0
#> 155 13.08 1 26 0 0
#> 36.1 21.19 1 48 0 1
#> 90.1 20.94 1 50 0 1
#> 81.1 14.06 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 16.1 8.71 1 71 0 1
#> 51 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 16.2 8.71 1 71 0 1
#> 157.1 15.10 1 47 0 0
#> 77.2 7.27 1 67 0 1
#> 68.2 20.62 1 44 0 0
#> 164.2 23.60 1 76 0 1
#> 92 22.92 1 47 0 1
#> 29.1 15.45 1 68 1 0
#> 36.2 21.19 1 48 0 1
#> 157.2 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 110.1 17.56 1 65 0 1
#> 145.1 10.07 1 65 1 0
#> 55 19.34 1 69 0 1
#> 14 12.89 1 21 0 0
#> 180.2 14.82 1 37 0 0
#> 99 21.19 1 38 0 1
#> 36.3 21.19 1 48 0 1
#> 4 17.64 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 197 21.60 1 69 1 0
#> 131 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 28 24.00 0 67 1 0
#> 122 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 118 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 22 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 44.1 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 115 24.00 0 NA 1 0
#> 95 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 193 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 53 24.00 0 32 0 1
#> 27 24.00 0 63 1 0
#> 148.1 24.00 0 61 1 0
#> 7 24.00 0 37 1 0
#> 62 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 62.1 24.00 0 71 0 0
#> 118.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 33 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 112.1 24.00 0 61 0 0
#> 112.2 24.00 0 61 0 0
#> 174 24.00 0 49 1 0
#> 17 24.00 0 38 0 1
#> 103.1 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 131.2 24.00 0 66 0 0
#> 115.1 24.00 0 NA 1 0
#> 146 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 147.1 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 75 24.00 0 21 1 0
#> 62.2 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 94.1 24.00 0 51 0 1
#> 74 24.00 0 43 0 1
#> 186 24.00 0 45 1 0
#> 198.1 24.00 0 66 0 1
#> 44.2 24.00 0 56 0 0
#> 98.1 24.00 0 34 1 0
#> 17.1 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 148.2 24.00 0 61 1 0
#> 118.2 24.00 0 44 1 0
#> 198.2 24.00 0 66 0 1
#> 174.1 24.00 0 49 1 0
#> 95.1 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 191.1 24.00 0 60 0 1
#> 1 24.00 0 23 1 0
#> 75.1 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 131.3 24.00 0 66 0 0
#> 1.1 24.00 0 23 1 0
#> 34 24.00 0 36 0 0
#> 135 24.00 0 58 1 0
#> 121.2 24.00 0 57 1 0
#> 198.3 24.00 0 66 0 1
#> 35 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 198.4 24.00 0 66 0 1
#> 198.5 24.00 0 66 0 1
#> 148.3 24.00 0 61 1 0
#> 198.6 24.00 0 66 0 1
#> 7.1 24.00 0 37 1 0
#> 9 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 1.06 NA NA NA
#> 2 age, Cure model -0.0197 NA NA NA
#> 3 grade_ii, Cure model -0.246 NA NA NA
#> 4 grade_iii, Cure model 0.590 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00318 NA NA NA
#> 2 grade_ii, Survival model 0.759 NA NA NA
#> 3 grade_iii, Survival model 0.301 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 1.06423 -0.01973 -0.24559 0.59023
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 254.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 1.06422584 -0.01972777 -0.24558705 0.59023055
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003176589 0.758942857 0.301012449
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.13189844 0.83174167 0.37414614 0.96285753 0.49323961 0.55867635
#> [7] 0.90242580 0.59341861 0.71834007 0.19572485 0.06815910 0.25442256
#> [13] 0.23183062 0.62763711 0.44352518 0.82379964 0.01158977 0.55867635
#> [19] 0.52115714 0.75911929 0.91018157 0.85542994 0.59341861 0.06815910
#> [25] 0.33427811 0.96285753 0.49323961 0.75093075 0.03581693 0.24333451
#> [31] 0.38422804 0.19572485 0.92539797 0.98523232 0.81579593 0.69404185
#> [37] 0.44352518 0.17030689 0.98523232 0.61900576 0.66112458 0.32414458
#> [43] 0.64441487 0.55867635 0.47315208 0.79984942 0.38422804 0.30362686
#> [49] 0.86334508 0.54928544 0.74272985 0.44352518 0.66951143 0.42367731
#> [55] 0.79984942 0.40394506 0.49323961 0.87906106 0.42367731 0.01158977
#> [61] 0.13189844 0.59341861 0.77544392 0.86334508 0.92539797 0.83174167
#> [67] 0.55867635 0.94043474 0.64441487 0.88693997 0.10493221 0.18295936
#> [73] 0.05227436 0.71834007 0.62763711 0.36411119 0.53987229 0.91018157
#> [79] 0.78357283 0.25442256 0.30362686 0.75911929 0.33427811 0.94043474
#> [85] 0.48319981 0.68588614 0.94043474 0.69404185 0.96285753 0.33427811
#> [91] 0.06815910 0.11853997 0.66951143 0.25442256 0.69404185 0.15778633
#> [97] 0.52115714 0.88693997 0.40394506 0.79170842 0.71834007 0.25442256
#> [103] 0.25442256 0.84750414 0.21988314 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 113 159 105 77 40 106 101 192 180 136 164 36 139
#> 22.86 10.55 19.75 7.27 18.00 16.67 9.97 16.44 14.82 21.83 23.60 21.19 21.49
#> 79 8 107 24 106.1 110 81 187 52 85 164.1 68 77.1
#> 16.23 18.43 11.18 23.89 16.67 17.56 14.06 9.92 10.42 16.44 23.60 20.62 7.27
#> 40.1 13 78 153 170 136.1 183 25 43 157 8.1 15 25.1
#> 18.00 14.34 23.88 21.33 19.54 21.83 9.24 6.32 12.10 15.10 18.43 22.68 6.32
#> 5 39 32 26 106.2 108 37 170.1 90 93 45 96 8.2
#> 16.43 15.59 20.90 15.77 16.67 18.29 12.52 19.54 20.94 10.33 17.42 14.54 18.43
#> 29 179 37.1 58 40.2 61 179.1 24.1 113.1 192.1 60 93.1 183.1
#> 15.45 18.63 12.52 19.34 18.00 10.12 18.63 23.89 22.86 16.44 13.15 10.33 9.24
#> 159.1 106.3 16 26.1 145 69 175 86 180.1 79.1 158 111 187.1
#> 10.55 16.67 8.71 15.77 10.07 23.23 21.91 23.81 14.82 16.23 20.14 17.45 9.92
#> 155 36.1 90.1 81.1 68.1 16.1 51 18 16.2 157.1 77.2 68.2 164.2
#> 13.08 21.19 20.94 14.06 20.62 8.71 18.23 15.21 8.71 15.10 7.27 20.62 23.60
#> 92 29.1 36.2 157.2 63 110.1 145.1 55 14 180.2 99 36.3 10
#> 22.92 15.45 21.19 15.10 22.77 17.56 10.07 19.34 12.89 14.82 21.19 21.19 10.53
#> 197 131 131.1 198 28 122 98 118 121 147 44 22 21
#> 21.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 44.1 116 95 148 193 191 53 27 148.1 7 62 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 103 152 156 62.1 118.1 82 33 104 94 112.1 112.2 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 103.1 38 131.2 146 121.1 147.1 65 75 62.2 143 31.1 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 74 186 198.1 44.2 98.1 17.1 156.1 148.2 118.2 198.2 174.1 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 173 191.1 1 75.1 185 83 131.3 1.1 34 135 121.2 198.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 132 198.4 198.5 148.3 198.6 7.1 9 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[48]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00149473 0.42337763 0.53523719
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.644886400 0.008025187 0.445925407
#> grade_iii, Cure model
#> 1.008826057
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 78 23.88 1 43 0 0
#> 107 11.18 1 54 1 0
#> 197 21.60 1 69 1 0
#> 69 23.23 1 25 0 1
#> 188 16.16 1 46 0 1
#> 107.1 11.18 1 54 1 0
#> 63 22.77 1 31 1 0
#> 168 23.72 1 70 0 0
#> 125 15.65 1 67 1 0
#> 117 17.46 1 26 0 1
#> 93 10.33 1 52 0 1
#> 57 14.46 1 45 0 1
#> 183 9.24 1 67 1 0
#> 149 8.37 1 33 1 0
#> 85 16.44 1 36 0 0
#> 37 12.52 1 57 1 0
#> 129 23.41 1 53 1 0
#> 169 22.41 1 46 0 0
#> 97 19.14 1 65 0 1
#> 188.1 16.16 1 46 0 1
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 66 22.13 1 53 0 0
#> 170 19.54 1 43 0 1
#> 70 7.38 1 30 1 0
#> 153 21.33 1 55 1 0
#> 155 13.08 1 26 0 0
#> 194 22.40 1 38 0 1
#> 86 23.81 1 58 0 1
#> 45 17.42 1 54 0 1
#> 153.1 21.33 1 55 1 0
#> 129.1 23.41 1 53 1 0
#> 194.1 22.40 1 38 0 1
#> 63.1 22.77 1 31 1 0
#> 149.1 8.37 1 33 1 0
#> 140 12.68 1 59 1 0
#> 45.1 17.42 1 54 0 1
#> 107.2 11.18 1 54 1 0
#> 8 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 187 9.92 1 39 1 0
#> 97.1 19.14 1 65 0 1
#> 16 8.71 1 71 0 1
#> 123 13.00 1 44 1 0
#> 39 15.59 1 37 0 1
#> 134 17.81 1 47 1 0
#> 59 10.16 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 187.1 9.92 1 39 1 0
#> 175 21.91 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 59.1 10.16 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 166 19.98 1 48 0 0
#> 57.1 14.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 170.1 19.54 1 43 0 1
#> 66.1 22.13 1 53 0 0
#> 78.1 23.88 1 43 0 0
#> 96 14.54 1 33 0 1
#> 16.1 8.71 1 71 0 1
#> 92 22.92 1 47 0 1
#> 49 12.19 1 48 1 0
#> 77 7.27 1 67 0 1
#> 6 15.64 1 39 0 0
#> 101 9.97 1 10 0 1
#> 110 17.56 1 65 0 1
#> 37.1 12.52 1 57 1 0
#> 139 21.49 1 63 1 0
#> 188.2 16.16 1 46 0 1
#> 117.1 17.46 1 26 0 1
#> 97.2 19.14 1 65 0 1
#> 8.1 18.43 1 32 0 0
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 114.1 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 140.1 12.68 1 59 1 0
#> 129.2 23.41 1 53 1 0
#> 110.1 17.56 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 78.2 23.88 1 43 0 0
#> 81 14.06 1 34 0 0
#> 184 17.77 1 38 0 0
#> 197.1 21.60 1 69 1 0
#> 139.1 21.49 1 63 1 0
#> 101.1 9.97 1 10 0 1
#> 124 9.73 1 NA 1 0
#> 155.1 13.08 1 26 0 0
#> 88 18.37 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 157 15.10 1 47 0 0
#> 76 19.22 1 54 0 1
#> 127 3.53 1 62 0 1
#> 177 12.53 1 75 0 0
#> 139.2 21.49 1 63 1 0
#> 85.1 16.44 1 36 0 0
#> 37.2 12.52 1 57 1 0
#> 111.1 17.45 1 47 0 1
#> 51.1 18.23 1 83 0 1
#> 192 16.44 1 31 1 0
#> 37.3 12.52 1 57 1 0
#> 149.2 8.37 1 33 1 0
#> 90 20.94 1 50 0 1
#> 30.1 17.43 1 78 0 0
#> 173 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 9 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 198 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 73 24.00 0 NA 0 1
#> 12.1 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 31 24.00 0 36 0 1
#> 174 24.00 0 49 1 0
#> 46 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 7.1 24.00 0 37 1 0
#> 112 24.00 0 61 0 0
#> 38 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 185.1 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 9.1 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 178 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 185.2 24.00 0 44 1 0
#> 12.2 24.00 0 63 0 0
#> 19.1 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 176 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 142 24.00 0 53 0 0
#> 143.1 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 162.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 67 24.00 0 25 0 0
#> 62 24.00 0 71 0 0
#> 104 24.00 0 50 1 0
#> 46.1 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 176.1 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 198.1 24.00 0 66 0 1
#> 142.1 24.00 0 53 0 0
#> 112.1 24.00 0 61 0 0
#> 178.1 24.00 0 52 1 0
#> 132 24.00 0 55 0 0
#> 46.2 24.00 0 71 0 0
#> 178.2 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 172 24.00 0 41 0 0
#> 173.2 24.00 0 19 0 1
#> 31.1 24.00 0 36 0 1
#> 191 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 98 24.00 0 34 1 0
#> 31.2 24.00 0 36 0 1
#> 198.2 24.00 0 66 0 1
#> 22.1 24.00 0 52 1 0
#> 143.2 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 65.1 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 62.1 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 116.1 24.00 0 58 0 1
#> 104.1 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 54.1 24.00 0 53 1 0
#> 182.1 24.00 0 35 0 0
#> 162.2 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 7.2 24.00 0 37 1 0
#> 67.1 24.00 0 25 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.645 NA NA NA
#> 2 age, Cure model 0.00803 NA NA NA
#> 3 grade_ii, Cure model 0.446 NA NA NA
#> 4 grade_iii, Cure model 1.01 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00149 NA NA NA
#> 2 grade_ii, Survival model 0.423 NA NA NA
#> 3 grade_iii, Survival model 0.535 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.644886 0.008025 0.445925 1.008826
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 252.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.644886400 0.008025187 0.445925407 1.008826057
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00149473 0.42337763 0.53523719
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.64758459 0.02477172 0.86895431 0.27112085 0.14978657 0.68075103
#> [7] 0.86895431 0.17719860 0.09041723 0.71311392 0.57994217 0.89135084
#> [13] 0.76114891 0.92824841 0.95006648 0.65598413 0.83118747 0.10927103
#> [19] 0.20132903 0.46309217 0.68075103 0.59710687 0.98580259 0.39557918
#> [25] 0.23652694 0.42507491 0.97149080 0.32472533 0.78457840 0.21383080
#> [31] 0.07195828 0.63091318 0.32472533 0.10927103 0.21383080 0.17719860
#> [37] 0.95006648 0.80800058 0.63091318 0.86895431 0.49921666 0.35576621
#> [43] 0.52660250 0.91359786 0.46309217 0.93558065 0.80018950 0.72928897
#> [49] 0.54450767 0.49005021 0.91359786 0.25939175 0.70499384 0.41522416
#> [55] 0.61398440 0.40539343 0.76114891 0.44402613 0.42507491 0.23652694
#> [61] 0.02477172 0.74536529 0.93558065 0.16383124 0.86134286 0.97866096
#> [67] 0.72119888 0.89884305 0.56244466 0.83118747 0.29336247 0.68075103
#> [73] 0.57994217 0.46309217 0.49921666 0.36596552 0.36596552 0.38561143
#> [79] 0.80800058 0.10927103 0.56244466 0.74536529 0.02477172 0.77673962
#> [85] 0.55347215 0.27112085 0.29336247 0.89884305 0.78457840 0.51741223
#> [91] 0.73732416 0.45361678 0.99291542 0.82342902 0.29336247 0.65598413
#> [97] 0.83118747 0.59710687 0.52660250 0.65598413 0.83118747 0.95006648
#> [103] 0.34543515 0.61398440 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 23 78 107 197 69 188 107.1 63 168 125 117 93 57
#> 16.92 23.88 11.18 21.60 23.23 16.16 11.18 22.77 23.72 15.65 17.46 10.33 14.46
#> 183 149 85 37 129 169 97 188.1 111 91 128 66 170
#> 9.24 8.37 16.44 12.52 23.41 22.41 19.14 16.16 17.45 5.33 20.35 22.13 19.54
#> 70 153 155 194 86 45 153.1 129.1 194.1 63.1 149.1 140 45.1
#> 7.38 21.33 13.08 22.40 23.81 17.42 21.33 23.41 22.40 22.77 8.37 12.68 17.42
#> 107.2 8 32 51 187 97.1 16 123 39 134 179 187.1 175
#> 11.18 18.43 20.90 18.23 9.92 19.14 8.71 13.00 15.59 17.81 18.63 9.92 21.91
#> 26 105 30 166 57.1 58 170.1 66.1 78.1 96 16.1 92 49
#> 15.77 19.75 17.43 19.98 14.46 19.34 19.54 22.13 23.88 14.54 8.71 22.92 12.19
#> 77 6 101 110 37.1 139 188.2 117.1 97.2 8.1 190 190.1 68
#> 7.27 15.64 9.97 17.56 12.52 21.49 16.16 17.46 19.14 18.43 20.81 20.81 20.62
#> 140.1 129.2 110.1 96.1 78.2 81 184 197.1 139.1 101.1 155.1 88 157
#> 12.68 23.41 17.56 14.54 23.88 14.06 17.77 21.60 21.49 9.97 13.08 18.37 15.10
#> 76 127 177 139.2 85.1 37.2 111.1 51.1 192 37.3 149.2 90 30.1
#> 19.22 3.53 12.53 21.49 16.44 12.52 17.45 18.23 16.44 12.52 8.37 20.94 17.43
#> 173 72 75 9 173.1 198 156 12 12.1 143 185 7 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 46 193 7.1 112 38 163 162 80 48 146 185.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 9.1 38.1 19 178 87 185.2 12.2 19.1 28 176 142 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 162.1 119 67 62 104 46.1 165 176.1 22 131 198.1 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 178.1 132 46.2 178.2 34 172 173.2 31.1 191 182 98 31.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.2 22.1 143.2 98.1 65.1 54 62.1 152 109 2 21 116.1 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 54.1 182.1 162.2 132.1 7.2 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[49]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006730044 0.524498356 0.313073212
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.339251827 0.007880567 0.072974942
#> grade_iii, Cure model
#> 0.479676130
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 111 17.45 1 47 0 1
#> 139 21.49 1 63 1 0
#> 133 14.65 1 57 0 0
#> 29 15.45 1 68 1 0
#> 23 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 140 12.68 1 59 1 0
#> 86 23.81 1 58 0 1
#> 39 15.59 1 37 0 1
#> 107 11.18 1 54 1 0
#> 130 16.47 1 53 0 1
#> 23.1 16.92 1 61 0 0
#> 107.1 11.18 1 54 1 0
#> 168 23.72 1 70 0 0
#> 188 16.16 1 46 0 1
#> 39.1 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 76 19.22 1 54 0 1
#> 154 12.63 1 20 1 0
#> 70 7.38 1 30 1 0
#> 180 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 59 10.16 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 175 21.91 1 43 0 0
#> 180.1 14.82 1 37 0 0
#> 96 14.54 1 33 0 1
#> 69 23.23 1 25 0 1
#> 175.1 21.91 1 43 0 0
#> 181 16.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 26 15.77 1 49 0 1
#> 140.1 12.68 1 59 1 0
#> 181.1 16.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 199 19.81 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 59.1 10.16 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 168.1 23.72 1 70 0 0
#> 66 22.13 1 53 0 0
#> 110 17.56 1 65 0 1
#> 150 20.33 1 48 0 0
#> 8 18.43 1 32 0 0
#> 96.1 14.54 1 33 0 1
#> 8.1 18.43 1 32 0 0
#> 13 14.34 1 54 0 1
#> 77 7.27 1 67 0 1
#> 168.2 23.72 1 70 0 0
#> 8.2 18.43 1 32 0 0
#> 4 17.64 1 NA 0 1
#> 25 6.32 1 34 1 0
#> 158 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 134 17.81 1 47 1 0
#> 41 18.02 1 40 1 0
#> 70.1 7.38 1 30 1 0
#> 69.1 23.23 1 25 0 1
#> 24 23.89 1 38 0 0
#> 25.1 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 184 17.77 1 38 0 0
#> 114.1 13.68 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 86.1 23.81 1 58 0 1
#> 97 19.14 1 65 0 1
#> 37 12.52 1 57 1 0
#> 155 13.08 1 26 0 0
#> 85.1 16.44 1 36 0 0
#> 125 15.65 1 67 1 0
#> 10 10.53 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 66.1 22.13 1 53 0 0
#> 93.1 10.33 1 52 0 1
#> 66.2 22.13 1 53 0 0
#> 190 20.81 1 42 1 0
#> 129 23.41 1 53 1 0
#> 134.1 17.81 1 47 1 0
#> 155.1 13.08 1 26 0 0
#> 91 5.33 1 61 0 1
#> 86.2 23.81 1 58 0 1
#> 45 17.42 1 54 0 1
#> 6 15.64 1 39 0 0
#> 55 19.34 1 69 0 1
#> 199.1 19.81 1 NA 0 1
#> 92 22.92 1 47 0 1
#> 90 20.94 1 50 0 1
#> 184.1 17.77 1 38 0 0
#> 106.1 16.67 1 49 1 0
#> 93.2 10.33 1 52 0 1
#> 40.1 18.00 1 28 1 0
#> 39.2 15.59 1 37 0 1
#> 4.1 17.64 1 NA 0 1
#> 24.1 23.89 1 38 0 0
#> 66.3 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 129.1 23.41 1 53 1 0
#> 16 8.71 1 71 0 1
#> 108 18.29 1 39 0 1
#> 180.2 14.82 1 37 0 0
#> 77.1 7.27 1 67 0 1
#> 13.1 14.34 1 54 0 1
#> 96.2 14.54 1 33 0 1
#> 153.1 21.33 1 55 1 0
#> 175.2 21.91 1 43 0 0
#> 79 16.23 1 54 1 0
#> 41.1 18.02 1 40 1 0
#> 187 9.92 1 39 1 0
#> 58 19.34 1 39 0 0
#> 55.1 19.34 1 69 0 1
#> 17 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 95 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 3 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 126 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 109 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 47 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 112 24.00 0 61 0 0
#> 80 24.00 0 41 0 0
#> 112.1 24.00 0 61 0 0
#> 186 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 87 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 135 24.00 0 58 1 0
#> 160.1 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 182.1 24.00 0 35 0 0
#> 109.1 24.00 0 48 0 0
#> 47.1 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 138 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 71 24.00 0 51 0 0
#> 112.2 24.00 0 61 0 0
#> 17.1 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 53.1 24.00 0 32 0 1
#> 115 24.00 0 NA 1 0
#> 191 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 186.1 24.00 0 45 1 0
#> 20.1 24.00 0 46 1 0
#> 74.1 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 165 24.00 0 47 0 0
#> 196.1 24.00 0 19 0 0
#> 138.1 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 131 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 102.1 24.00 0 49 0 0
#> 116.1 24.00 0 58 0 1
#> 115.1 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 74.2 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 47.2 24.00 0 38 0 1
#> 141.1 24.00 0 44 1 0
#> 138.2 24.00 0 44 1 0
#> 17.2 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 44.1 24.00 0 56 0 0
#> 33 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 147.1 24.00 0 76 1 0
#> 28 24.00 0 67 1 0
#> 115.2 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 62.1 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 94 24.00 0 51 0 1
#> 126.1 24.00 0 48 0 0
#> 38.1 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 200.1 24.00 0 64 0 0
#> 87.1 24.00 0 27 0 0
#> 103.1 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.339 NA NA NA
#> 2 age, Cure model 0.00788 NA NA NA
#> 3 grade_ii, Cure model 0.0730 NA NA NA
#> 4 grade_iii, Cure model 0.480 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00673 NA NA NA
#> 2 grade_ii, Survival model 0.524 NA NA NA
#> 3 grade_iii, Survival model 0.313 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.339252 0.007881 0.072975 0.479676
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 254.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.339251827 0.007880567 0.072974942 0.479676130
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006730044 0.524498356 0.313073212
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.443339911 0.199084132 0.690514250 0.650907500 0.472870773 0.810398322
#> [7] 0.780383925 0.021626298 0.621508381 0.840569976 0.522276673 0.472870773
#> [13] 0.840569976 0.043269786 0.581638215 0.621508381 0.375868651 0.296357598
#> [19] 0.800391326 0.930616137 0.660848058 0.189038625 0.453122068 0.160441092
#> [25] 0.660848058 0.700594747 0.088674822 0.160441092 0.532203014 0.115943435
#> [31] 0.591600578 0.780383925 0.532203014 0.551863175 0.492699556 0.043269786
#> [37] 0.125036943 0.433558460 0.247827485 0.316354805 0.700594747 0.316354805
#> [43] 0.730283086 0.950444734 0.043269786 0.316354805 0.970326754 0.257649809
#> [49] 0.512358384 0.870603711 0.395175436 0.356157787 0.930616137 0.088674822
#> [55] 0.005944646 0.970326754 0.209076447 0.414266575 0.910533516 0.021626298
#> [61] 0.306337105 0.830484155 0.750238670 0.551863175 0.601565723 0.860537384
#> [67] 0.810398322 0.125036943 0.870603711 0.125036943 0.238111501 0.070206377
#> [73] 0.395175436 0.750238670 0.990069618 0.021626298 0.462991246 0.611518283
#> [79] 0.267462143 0.106577608 0.228285900 0.414266575 0.492699556 0.870603711
#> [85] 0.375868651 0.621508381 0.005944646 0.125036943 0.770279853 0.070206377
#> [91] 0.920566507 0.345996357 0.660848058 0.950444734 0.730283086 0.700594747
#> [97] 0.209076447 0.160441092 0.571675260 0.356157787 0.900492077 0.267462143
#> [103] 0.267462143 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 111 139 133 29 23 177 140 86 39 107 130 23.1 107.1
#> 17.45 21.49 14.65 15.45 16.92 12.53 12.68 23.81 15.59 11.18 16.47 16.92 11.18
#> 168 188 39.1 40 76 154 70 180 136 30 175 180.1 96
#> 23.72 16.16 15.59 18.00 19.22 12.63 7.38 14.82 21.83 17.43 21.91 14.82 14.54
#> 69 175.1 181 63 26 140.1 181.1 85 106 168.1 66 110 150
#> 23.23 21.91 16.46 22.77 15.77 12.68 16.46 16.44 16.67 23.72 22.13 17.56 20.33
#> 8 96.1 8.1 13 77 168.2 8.2 25 158 171 93 134 41
#> 18.43 14.54 18.43 14.34 7.27 23.72 18.43 6.32 20.14 16.57 10.33 17.81 18.02
#> 70.1 69.1 24 25.1 153 184 183 86.1 97 37 155 85.1 125
#> 7.38 23.23 23.89 6.32 21.33 17.77 9.24 23.81 19.14 12.52 13.08 16.44 15.65
#> 10 177.1 66.1 93.1 66.2 190 129 134.1 155.1 91 86.2 45 6
#> 10.53 12.53 22.13 10.33 22.13 20.81 23.41 17.81 13.08 5.33 23.81 17.42 15.64
#> 55 92 90 184.1 106.1 93.2 40.1 39.2 24.1 66.3 14 129.1 16
#> 19.34 22.92 20.94 17.77 16.67 10.33 18.00 15.59 23.89 22.13 12.89 23.41 8.71
#> 108 180.2 77.1 13.1 96.2 153.1 175.2 79 41.1 187 58 55.1 17
#> 18.29 14.82 7.27 14.34 14.54 21.33 21.91 16.23 18.02 9.92 19.34 19.34 24.00
#> 74 20 95 116 3 53 126 182 109 160 62 200 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 112 80 112.1 186 87 118 38 162 146 147 44 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 1 182.1 109.1 47.1 143 193 138 141 103 71 112.2 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 72 53.1 191 120 196 186.1 20.1 74.1 102 165 196.1 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 2 131 178 102.1 116.1 12 74.2 19 47.2 141.1 138.2 17.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 44.1 33 75 34 147.1 28 148 62.1 48 7 94 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 191.1 200.1 87.1 103.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[50]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003835261 0.456755654 0.374541251
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.63924629 0.01386856 -0.18979675
#> grade_iii, Cure model
#> 0.76021312
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 164 23.60 1 76 0 1
#> 181 16.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 24 23.89 1 38 0 0
#> 23 16.92 1 61 0 0
#> 68 20.62 1 44 0 0
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 164.1 23.60 1 76 0 1
#> 69 23.23 1 25 0 1
#> 60 13.15 1 38 1 0
#> 192 16.44 1 31 1 0
#> 184 17.77 1 38 0 0
#> 125 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 129 23.41 1 53 1 0
#> 26 15.77 1 49 0 1
#> 117 17.46 1 26 0 1
#> 52 10.42 1 52 0 1
#> 157 15.10 1 47 0 0
#> 197 21.60 1 69 1 0
#> 57 14.46 1 45 0 1
#> 117.1 17.46 1 26 0 1
#> 181.1 16.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 188 16.16 1 46 0 1
#> 6.1 15.64 1 39 0 0
#> 167 15.55 1 56 1 0
#> 127 3.53 1 62 0 1
#> 183 9.24 1 67 1 0
#> 167.1 15.55 1 56 1 0
#> 123 13.00 1 44 1 0
#> 39.1 15.59 1 37 0 1
#> 39.2 15.59 1 37 0 1
#> 111 17.45 1 47 0 1
#> 6.2 15.64 1 39 0 0
#> 25 6.32 1 34 1 0
#> 117.2 17.46 1 26 0 1
#> 91 5.33 1 61 0 1
#> 136 21.83 1 43 0 1
#> 166 19.98 1 48 0 0
#> 14 12.89 1 21 0 0
#> 93 10.33 1 52 0 1
#> 177 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 77 7.27 1 67 0 1
#> 60.1 13.15 1 38 1 0
#> 30 17.43 1 78 0 0
#> 140 12.68 1 59 1 0
#> 129.1 23.41 1 53 1 0
#> 10 10.53 1 34 0 0
#> 133 14.65 1 57 0 0
#> 6.3 15.64 1 39 0 0
#> 110 17.56 1 65 0 1
#> 85 16.44 1 36 0 0
#> 111.1 17.45 1 47 0 1
#> 139 21.49 1 63 1 0
#> 189 10.51 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 139.1 21.49 1 63 1 0
#> 36 21.19 1 48 0 1
#> 171 16.57 1 41 0 1
#> 42 12.43 1 49 0 1
#> 189.1 10.51 1 NA 1 0
#> 183.1 9.24 1 67 1 0
#> 8 18.43 1 32 0 0
#> 52.1 10.42 1 52 0 1
#> 164.2 23.60 1 76 0 1
#> 150 20.33 1 48 0 0
#> 58 19.34 1 39 0 0
#> 157.1 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 139.2 21.49 1 63 1 0
#> 18 15.21 1 49 1 0
#> 66 22.13 1 53 0 0
#> 18.1 15.21 1 49 1 0
#> 16.1 8.71 1 71 0 1
#> 197.1 21.60 1 69 1 0
#> 168 23.72 1 70 0 0
#> 16.2 8.71 1 71 0 1
#> 179 18.63 1 42 0 0
#> 30.1 17.43 1 78 0 0
#> 15 22.68 1 48 0 0
#> 25.1 6.32 1 34 1 0
#> 93.1 10.33 1 52 0 1
#> 5 16.43 1 51 0 1
#> 125.1 15.65 1 67 1 0
#> 30.2 17.43 1 78 0 0
#> 58.1 19.34 1 39 0 0
#> 100 16.07 1 60 0 0
#> 170 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 133.1 14.65 1 57 0 0
#> 183.2 9.24 1 67 1 0
#> 24.1 23.89 1 38 0 0
#> 181.2 16.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 108.1 18.29 1 39 0 1
#> 154.1 12.63 1 20 1 0
#> 10.1 10.53 1 34 0 0
#> 166.1 19.98 1 48 0 0
#> 167.2 15.55 1 56 1 0
#> 136.1 21.83 1 43 0 1
#> 133.2 14.65 1 57 0 0
#> 133.3 14.65 1 57 0 0
#> 159 10.55 1 50 0 1
#> 199 19.81 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 188.1 16.16 1 46 0 1
#> 78 23.88 1 43 0 0
#> 97 19.14 1 65 0 1
#> 138 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 126 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 44 24.00 0 56 0 0
#> 163 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 75 24.00 0 21 1 0
#> 148 24.00 0 61 1 0
#> 75.1 24.00 0 21 1 0
#> 33 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 174 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 95 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 163.2 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 138.1 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 22 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 87.1 24.00 0 27 0 0
#> 141 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 48 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 67.1 24.00 0 25 0 0
#> 120 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 75.2 24.00 0 21 1 0
#> 116 24.00 0 58 0 1
#> 3 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 193 24.00 0 45 0 1
#> 178.1 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#> 109 24.00 0 48 0 0
#> 72.1 24.00 0 40 0 1
#> 162 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 193.1 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 198.1 24.00 0 66 0 1
#> 104 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 182 24.00 0 35 0 0
#> 196.1 24.00 0 19 0 0
#> 82 24.00 0 34 0 0
#> 132 24.00 0 55 0 0
#> 98 24.00 0 34 1 0
#> 148.1 24.00 0 61 1 0
#> 28.1 24.00 0 67 1 0
#> 33.1 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 178.2 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 185.1 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 9.1 24.00 0 31 1 0
#> 185.2 24.00 0 44 1 0
#> 185.3 24.00 0 44 1 0
#> 132.2 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 122.1 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 143.1 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 163.3 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 104.1 24.00 0 50 1 0
#> 72.2 24.00 0 40 0 1
#> 126.1 24.00 0 48 0 0
#> 31.1 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 72.3 24.00 0 40 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.639 NA NA NA
#> 2 age, Cure model 0.0139 NA NA NA
#> 3 grade_ii, Cure model -0.190 NA NA NA
#> 4 grade_iii, Cure model 0.760 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00384 NA NA NA
#> 2 grade_ii, Survival model 0.457 NA NA NA
#> 3 grade_iii, Survival model 0.375 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.63925 0.01387 -0.18980 0.76021
#>
#> Degrees of Freedom: 195 Total (i.e. Null); 192 Residual
#> Null Deviance: 269.7
#> Residual Deviance: 260.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.63924629 0.01386856 -0.18979675 0.76021312
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003835261 0.456755654 0.374541251
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.805596393 0.054270204 0.479485931 0.340525816 0.008582324 0.451461882
#> [7] 0.235425389 0.587343896 0.622627788 0.054270204 0.106309443 0.762206850
#> [13] 0.506481061 0.359356434 0.569579593 0.933155784 0.085493873 0.560564436
#> [19] 0.378476380 0.874064692 0.692412341 0.178754616 0.753413535 0.378476380
#> [25] 0.479485931 0.245009044 0.533637575 0.587343896 0.648987380 0.991656799
#> [31] 0.908013993 0.648987380 0.779546941 0.622627788 0.622627788 0.405755669
#> [37] 0.587343896 0.966645996 0.378476380 0.983303299 0.158763613 0.264034776
#> [43] 0.788233319 0.891070278 0.822672667 0.148110555 0.958224912 0.762206850
#> [49] 0.423975014 0.796927112 0.085493873 0.856995563 0.709839482 0.587343896
#> [55] 0.368932926 0.506481061 0.405755669 0.198285664 0.744597194 0.198285664
#> [61] 0.225901979 0.470193998 0.831278020 0.908013993 0.330839713 0.874064692
#> [67] 0.054270204 0.254491998 0.292574423 0.692412341 0.116932506 0.198285664
#> [73] 0.675057269 0.137573002 0.675057269 0.933155784 0.178754616 0.040233050
#> [79] 0.933155784 0.321186270 0.423975014 0.127182162 0.966645996 0.891070278
#> [85] 0.524553224 0.569579593 0.423975014 0.292574423 0.551519440 0.283002276
#> [91] 0.709839482 0.908013993 0.008582324 0.479485931 0.460857290 0.340525816
#> [97] 0.805596393 0.856995563 0.264034776 0.648987380 0.158763613 0.709839482
#> [103] 0.709839482 0.848439020 0.839865136 0.533637575 0.027292173 0.311575819
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 154 164 181 108 24 23 68 6 39 164.1 69 60 192
#> 12.63 23.60 16.46 18.29 23.89 16.92 20.62 15.64 15.59 23.60 23.23 13.15 16.44
#> 184 125 16 129 26 117 52 157 197 57 117.1 181.1 128
#> 17.77 15.65 8.71 23.41 15.77 17.46 10.42 15.10 21.60 14.46 17.46 16.46 20.35
#> 188 6.1 167 127 183 167.1 123 39.1 39.2 111 6.2 25 117.2
#> 16.16 15.64 15.55 3.53 9.24 15.55 13.00 15.59 15.59 17.45 15.64 6.32 17.46
#> 91 136 166 14 93 177 175 77 60.1 30 140 129.1 10
#> 5.33 21.83 19.98 12.89 10.33 12.53 21.91 7.27 13.15 17.43 12.68 23.41 10.53
#> 133 6.3 110 85 111.1 139 96 139.1 36 171 42 183.1 8
#> 14.65 15.64 17.56 16.44 17.45 21.49 14.54 21.49 21.19 16.57 12.43 9.24 18.43
#> 52.1 164.2 150 58 157.1 63 139.2 18 66 18.1 16.1 197.1 168
#> 10.42 23.60 20.33 19.34 15.10 22.77 21.49 15.21 22.13 15.21 8.71 21.60 23.72
#> 16.2 179 30.1 15 25.1 93.1 5 125.1 30.2 58.1 100 170 133.1
#> 8.71 18.63 17.43 22.68 6.32 10.33 16.43 15.65 17.43 19.34 16.07 19.54 14.65
#> 183.2 24.1 181.2 106 108.1 154.1 10.1 166.1 167.2 136.1 133.2 133.3 159
#> 9.24 23.89 16.46 16.67 18.29 12.63 10.53 19.98 15.55 21.83 14.65 14.65 10.55
#> 43 188.1 78 97 138 196 126 173 44 163 178 122 163.1
#> 12.10 16.16 23.88 19.14 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 75 148 75.1 33 172 174 87 95 135 163.2 173.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 67 22 72 87.1 141 160 53 48 95.1 62 67.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 75.2 116 3 71 3.1 28 193 178.1 200 109 72.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 193.1 2 198.1 104 103 182 196.1 82 132 98 148.1 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 156 178.2 185 31 9 185.1 143 132.1 9.1 185.2 185.3 132.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 172.1 122.1 116.1 143.1 165 163.3 27 104.1 72.2 126.1 31.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.3
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[51]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01966676 0.88580834 -0.08474149
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.344895168 0.009397877 -0.205973821
#> grade_iii, Cure model
#> 0.550003175
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 108 18.29 1 39 0 1
#> 164 23.60 1 76 0 1
#> 179 18.63 1 42 0 0
#> 68 20.62 1 44 0 0
#> 96 14.54 1 33 0 1
#> 25 6.32 1 34 1 0
#> 26 15.77 1 49 0 1
#> 15 22.68 1 48 0 0
#> 111 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 42 12.43 1 49 0 1
#> 164.1 23.60 1 76 0 1
#> 145 10.07 1 65 1 0
#> 25.1 6.32 1 34 1 0
#> 111.1 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 168 23.72 1 70 0 0
#> 167 15.55 1 56 1 0
#> 58 19.34 1 39 0 0
#> 18 15.21 1 49 1 0
#> 105 19.75 1 60 0 0
#> 56 12.21 1 60 0 0
#> 175 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 189 10.51 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 155 13.08 1 26 0 0
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 157 15.10 1 47 0 0
#> 60 13.15 1 38 1 0
#> 45 17.42 1 54 0 1
#> 184 17.77 1 38 0 0
#> 81 14.06 1 34 0 0
#> 168.1 23.72 1 70 0 0
#> 45.1 17.42 1 54 0 1
#> 70 7.38 1 30 1 0
#> 190 20.81 1 42 1 0
#> 58.1 19.34 1 39 0 0
#> 184.1 17.77 1 38 0 0
#> 60.1 13.15 1 38 1 0
#> 127 3.53 1 62 0 1
#> 77 7.27 1 67 0 1
#> 5 16.43 1 51 0 1
#> 70.1 7.38 1 30 1 0
#> 58.2 19.34 1 39 0 0
#> 97 19.14 1 65 0 1
#> 92 22.92 1 47 0 1
#> 149 8.37 1 33 1 0
#> 88 18.37 1 47 0 0
#> 37 12.52 1 57 1 0
#> 57 14.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 69 23.23 1 25 0 1
#> 183 9.24 1 67 1 0
#> 184.2 17.77 1 38 0 0
#> 170 19.54 1 43 0 1
#> 90 20.94 1 50 0 1
#> 140 12.68 1 59 1 0
#> 140.1 12.68 1 59 1 0
#> 153 21.33 1 55 1 0
#> 110 17.56 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 136.1 21.83 1 43 0 1
#> 100 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 123 13.00 1 44 1 0
#> 117 17.46 1 26 0 1
#> 195 11.76 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 70.2 7.38 1 30 1 0
#> 6.1 15.64 1 39 0 0
#> 90.1 20.94 1 50 0 1
#> 10.1 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 111.2 17.45 1 47 0 1
#> 164.2 23.60 1 76 0 1
#> 150 20.33 1 48 0 0
#> 197 21.60 1 69 1 0
#> 93 10.33 1 52 0 1
#> 145.1 10.07 1 65 1 0
#> 133 14.65 1 57 0 0
#> 41 18.02 1 40 1 0
#> 158 20.14 1 74 1 0
#> 128 20.35 1 35 0 1
#> 58.3 19.34 1 39 0 0
#> 170.1 19.54 1 43 0 1
#> 195.1 11.76 1 NA 1 0
#> 6.2 15.64 1 39 0 0
#> 40 18.00 1 28 1 0
#> 157.1 15.10 1 47 0 0
#> 194 22.40 1 38 0 1
#> 5.1 16.43 1 51 0 1
#> 45.2 17.42 1 54 0 1
#> 125 15.65 1 67 1 0
#> 106.1 16.67 1 49 1 0
#> 88.1 18.37 1 47 0 0
#> 155.1 13.08 1 26 0 0
#> 188 16.16 1 46 0 1
#> 183.1 9.24 1 67 1 0
#> 110.1 17.56 1 65 0 1
#> 86 23.81 1 58 0 1
#> 127.1 3.53 1 62 0 1
#> 99.1 21.19 1 38 0 1
#> 113 22.86 1 34 0 0
#> 29 15.45 1 68 1 0
#> 157.2 15.10 1 47 0 0
#> 101.1 9.97 1 10 0 1
#> 97.1 19.14 1 65 0 1
#> 91 5.33 1 61 0 1
#> 77.1 7.27 1 67 0 1
#> 173 24.00 0 19 0 1
#> 200 24.00 0 64 0 0
#> 71 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 67 24.00 0 25 0 0
#> 38 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 185 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 109 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 65 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 118 24.00 0 44 1 0
#> 72.1 24.00 0 40 0 1
#> 11 24.00 0 42 0 1
#> 12 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 182.1 24.00 0 35 0 0
#> 98 24.00 0 34 1 0
#> 21 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 74.1 24.00 0 43 0 1
#> 173.1 24.00 0 19 0 1
#> 22 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 144 24.00 0 28 0 1
#> 109.1 24.00 0 48 0 0
#> 21.1 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 200.1 24.00 0 64 0 0
#> 46.1 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 118.1 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 146 24.00 0 63 1 0
#> 191 24.00 0 60 0 1
#> 121 24.00 0 57 1 0
#> 131.1 24.00 0 66 0 0
#> 74.2 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 3 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 126 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 22.1 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 200.2 24.00 0 64 0 0
#> 2 24.00 0 9 0 0
#> 31.1 24.00 0 36 0 1
#> 116.1 24.00 0 58 0 1
#> 174.1 24.00 0 49 1 0
#> 172 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 1.1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 94 24.00 0 51 0 1
#> 165 24.00 0 47 0 0
#> 165.1 24.00 0 47 0 0
#> 193 24.00 0 45 0 1
#> 28 24.00 0 67 1 0
#> 11.1 24.00 0 42 0 1
#> 67.1 24.00 0 25 0 0
#> 54.1 24.00 0 53 1 0
#> 148 24.00 0 61 1 0
#> 64 24.00 0 43 0 0
#> 146.1 24.00 0 63 1 0
#> 144.1 24.00 0 28 0 1
#> 22.2 24.00 0 52 1 0
#> 193.1 24.00 0 45 0 1
#> 95 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 9.1 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 12.1 24.00 0 63 0 0
#> 22.3 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 116.2 24.00 0 58 0 1
#> 148.1 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.345 NA NA NA
#> 2 age, Cure model 0.00940 NA NA NA
#> 3 grade_ii, Cure model -0.206 NA NA NA
#> 4 grade_iii, Cure model 0.550 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0197 NA NA NA
#> 2 grade_ii, Survival model 0.886 NA NA NA
#> 3 grade_iii, Survival model -0.0847 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.344895 0.009398 -0.205974 0.550003
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 259.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.344895168 0.009397877 -0.205973821 0.550003175
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01966676 0.88580834 -0.08474149
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.077937e-01 1.089906e-04 8.851382e-02 2.983279e-02 4.440868e-01
#> [6] 9.166509e-01 2.978194e-01 3.265321e-03 1.729877e-01 3.206015e-01
#> [11] 6.128275e-01 1.089906e-04 7.054935e-01 9.166509e-01 1.729877e-01
#> [16] 8.903745e-06 3.557290e-01 5.752127e-02 3.802733e-01 4.443467e-02
#> [21] 6.277676e-01 5.831691e-03 5.834885e-01 7.438503e-03 5.129292e-01
#> [26] 6.429581e-01 7.376579e-01 3.926500e-01 4.855119e-01 1.982561e-01
#> [31] 1.285104e-01 4.714850e-01 8.903745e-06 1.982561e-01 8.360005e-01
#> [36] 2.668348e-02 5.752127e-02 1.285104e-01 4.855119e-01 9.660424e-01
#> [41] 8.836735e-01 2.554149e-01 8.360005e-01 5.752127e-02 7.693554e-02
#> [46] 1.501415e-03 8.194669e-01 9.474292e-02 5.981203e-01 4.576586e-01
#> [51] 7.701702e-01 9.057589e-04 7.865576e-01 1.285104e-01 4.862045e-02
#> [56] 2.071670e-02 5.551332e-01 5.551332e-01 1.341132e-02 1.494799e-01
#> [61] 7.438503e-03 2.867745e-01 6.736799e-01 5.409462e-01 1.649095e-01
#> [66] 2.358591e-01 8.360005e-01 3.206015e-01 2.071670e-02 6.429581e-01
#> [71] 2.259331e-01 1.570097e-02 1.729877e-01 1.089906e-04 3.673506e-02
#> [76] 1.118988e-02 6.894639e-01 7.054935e-01 4.307272e-01 1.147798e-01
#> [81] 4.050538e-02 3.318731e-02 5.752127e-02 4.862045e-02 3.206015e-01
#> [86] 1.217221e-01 3.926500e-01 4.444000e-03 2.554149e-01 1.982561e-01
#> [91] 3.091368e-01 2.358591e-01 9.474292e-02 5.129292e-01 2.760167e-01
#> [96] 7.865576e-01 1.494799e-01 2.954956e-07 9.660424e-01 1.570097e-02
#> [101] 2.300602e-03 3.679268e-01 3.926500e-01 7.376579e-01 7.693554e-02
#> [106] 9.493433e-01 8.836735e-01 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 108 164 179 68 96 25 26 15 111 6 42 164.1 145
#> 18.29 23.60 18.63 20.62 14.54 6.32 15.77 22.68 17.45 15.64 12.43 23.60 10.07
#> 25.1 111.1 168 167 58 18 105 56 175 177 136 155 10
#> 6.32 17.45 23.72 15.55 19.34 15.21 19.75 12.21 21.91 12.53 21.83 13.08 10.53
#> 101 157 60 45 184 81 168.1 45.1 70 190 58.1 184.1 60.1
#> 9.97 15.10 13.15 17.42 17.77 14.06 23.72 17.42 7.38 20.81 19.34 17.77 13.15
#> 127 77 5 70.1 58.2 97 92 149 88 37 57 187 69
#> 3.53 7.27 16.43 7.38 19.34 19.14 22.92 8.37 18.37 12.52 14.46 9.92 23.23
#> 183 184.2 170 90 140 140.1 153 110 136.1 100 52 123 117
#> 9.24 17.77 19.54 20.94 12.68 12.68 21.33 17.56 21.83 16.07 10.42 13.00 17.46
#> 106 70.2 6.1 90.1 10.1 23 99 111.2 164.2 150 197 93 145.1
#> 16.67 7.38 15.64 20.94 10.53 16.92 21.19 17.45 23.60 20.33 21.60 10.33 10.07
#> 133 41 158 128 58.3 170.1 6.2 40 157.1 194 5.1 45.2 125
#> 14.65 18.02 20.14 20.35 19.34 19.54 15.64 18.00 15.10 22.40 16.43 17.42 15.65
#> 106.1 88.1 155.1 188 183.1 110.1 86 127.1 99.1 113 29 157.2 101.1
#> 16.67 18.37 13.08 16.16 9.24 17.56 23.81 3.53 21.19 22.86 15.45 15.10 9.97
#> 97.1 91 77.1 173 200 71 46 72 67 38 174 185 182
#> 19.14 5.33 7.27 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 131 102 65 54 118 72.1 11 12 48 74 182.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 35 186 74.1 173.1 22 120 144 109.1 21.1 1 200.1 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 118.1 7 146 191 121 131.1 74.2 147 3 126 116 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 87 200.2 2 31.1 116.1 174.1 172 156 34 1.1 9 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 165 165.1 193 28 11.1 67.1 54.1 148 64 146.1 144.1 22.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 95 163 142 9.1 178 12.1 22.3 160 116.2 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[52]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01922852 0.90906190 0.43895698
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.6964157784 0.0144748392 0.0001377768
#> grade_iii, Cure model
#> 0.5720638515
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 145 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 86 23.81 1 58 0 1
#> 181 16.46 1 45 0 1
#> 66 22.13 1 53 0 0
#> 117 17.46 1 26 0 1
#> 105 19.75 1 60 0 0
#> 36 21.19 1 48 0 1
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 52 10.42 1 52 0 1
#> 77 7.27 1 67 0 1
#> 114 13.68 1 NA 0 0
#> 179 18.63 1 42 0 0
#> 149 8.37 1 33 1 0
#> 52.1 10.42 1 52 0 1
#> 153 21.33 1 55 1 0
#> 117.1 17.46 1 26 0 1
#> 92 22.92 1 47 0 1
#> 188 16.16 1 46 0 1
#> 190 20.81 1 42 1 0
#> 133 14.65 1 57 0 0
#> 175 21.91 1 43 0 0
#> 164 23.60 1 76 0 1
#> 114.1 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 90 20.94 1 50 0 1
#> 36.1 21.19 1 48 0 1
#> 32 20.90 1 37 1 0
#> 79 16.23 1 54 1 0
#> 139 21.49 1 63 1 0
#> 61 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 81.1 14.06 1 34 0 0
#> 175.1 21.91 1 43 0 0
#> 187 9.92 1 39 1 0
#> 85.1 16.44 1 36 0 0
#> 106 16.67 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 188.1 16.16 1 46 0 1
#> 170 19.54 1 43 0 1
#> 91 5.33 1 61 0 1
#> 24 23.89 1 38 0 0
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 170.1 19.54 1 43 0 1
#> 179.1 18.63 1 42 0 0
#> 86.1 23.81 1 58 0 1
#> 154 12.63 1 20 1 0
#> 111.1 17.45 1 47 0 1
#> 56 12.21 1 60 0 0
#> 180.1 14.82 1 37 0 0
#> 128 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 49 12.19 1 48 1 0
#> 78 23.88 1 43 0 0
#> 13 14.34 1 54 0 1
#> 129 23.41 1 53 1 0
#> 78.1 23.88 1 43 0 0
#> 26 15.77 1 49 0 1
#> 194.1 22.40 1 38 0 1
#> 158 20.14 1 74 1 0
#> 134 17.81 1 47 1 0
#> 159 10.55 1 50 0 1
#> 25 6.32 1 34 1 0
#> 167 15.55 1 56 1 0
#> 97 19.14 1 65 0 1
#> 168 23.72 1 70 0 0
#> 149.1 8.37 1 33 1 0
#> 5 16.43 1 51 0 1
#> 92.1 22.92 1 47 0 1
#> 113 22.86 1 34 0 0
#> 124.1 9.73 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 55 19.34 1 69 0 1
#> 139.1 21.49 1 63 1 0
#> 81.2 14.06 1 34 0 0
#> 36.2 21.19 1 48 0 1
#> 158.1 20.14 1 74 1 0
#> 127.1 3.53 1 62 0 1
#> 8 18.43 1 32 0 0
#> 96 14.54 1 33 0 1
#> 110 17.56 1 65 0 1
#> 125 15.65 1 67 1 0
#> 88 18.37 1 47 0 0
#> 18 15.21 1 49 1 0
#> 130 16.47 1 53 0 1
#> 26.1 15.77 1 49 0 1
#> 123.1 13.00 1 44 1 0
#> 167.1 15.55 1 56 1 0
#> 36.3 21.19 1 48 0 1
#> 150 20.33 1 48 0 0
#> 25.1 6.32 1 34 1 0
#> 78.2 23.88 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 26.2 15.77 1 49 0 1
#> 56.1 12.21 1 60 0 0
#> 124.2 9.73 1 NA 1 0
#> 25.2 6.32 1 34 1 0
#> 70 7.38 1 30 1 0
#> 110.1 17.56 1 65 0 1
#> 153.1 21.33 1 55 1 0
#> 8.1 18.43 1 32 0 0
#> 124.3 9.73 1 NA 1 0
#> 81.3 14.06 1 34 0 0
#> 169 22.41 1 46 0 0
#> 86.2 23.81 1 58 0 1
#> 188.2 16.16 1 46 0 1
#> 81.4 14.06 1 34 0 0
#> 100.1 16.07 1 60 0 0
#> 174 24.00 0 49 1 0
#> 135 24.00 0 58 1 0
#> 47 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 162 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 47.1 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 33 24.00 0 53 0 0
#> 176 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 33.1 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 122.1 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 126 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 193 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 191 24.00 0 60 0 1
#> 53 24.00 0 32 0 1
#> 47.2 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 64 24.00 0 43 0 0
#> 147 24.00 0 76 1 0
#> 1 24.00 0 23 1 0
#> 11.1 24.00 0 42 0 1
#> 53.1 24.00 0 32 0 1
#> 71.1 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 3.1 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 191.1 24.00 0 60 0 1
#> 33.2 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 126.1 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 151 24.00 0 42 0 0
#> 193.2 24.00 0 45 0 1
#> 200 24.00 0 64 0 0
#> 64.1 24.00 0 43 0 0
#> 38.1 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 135.1 24.00 0 58 1 0
#> 35.1 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 115.1 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 84 24.00 0 39 0 1
#> 200.1 24.00 0 64 0 0
#> 83.1 24.00 0 6 0 0
#> 65.1 24.00 0 57 1 0
#> 173.1 24.00 0 19 0 1
#> 176.1 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 144.1 24.00 0 28 0 1
#> 178.1 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 31 24.00 0 36 0 1
#> 3.2 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 71.2 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 147.1 24.00 0 76 1 0
#> 9 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 104 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 142 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 94.2 24.00 0 51 0 1
#> 27 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.696 NA NA NA
#> 2 age, Cure model 0.0145 NA NA NA
#> 3 grade_ii, Cure model 0.000138 NA NA NA
#> 4 grade_iii, Cure model 0.572 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0192 NA NA NA
#> 2 grade_ii, Survival model 0.909 NA NA NA
#> 3 grade_iii, Survival model 0.439 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.6964158 0.0144748 0.0001378 0.5720639
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 256.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.6964157784 0.0144748392 0.0001377768 0.5720638515
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01922852 0.90906190 0.43895698
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 8.174535e-01 9.714577e-01 3.741390e-03 3.526701e-01 4.560221e-02
#> [6] 2.812834e-01 1.647397e-01 8.735874e-02 3.010790e-01 5.493419e-01
#> [11] 7.751338e-01 8.880019e-01 2.060326e-01 8.460096e-01 7.751338e-01
#> [16] 7.486315e-02 2.812834e-01 1.936105e-02 4.072636e-01 1.277231e-01
#> [21] 5.744783e-01 5.103819e-02 1.221419e-02 6.134027e-01 1.132271e-01
#> [26] 8.735874e-02 1.205226e-01 3.961096e-01 6.265284e-02 8.032261e-01
#> [31] 3.633403e-01 6.134027e-01 5.103819e-02 8.317527e-01 3.633403e-01
#> [36] 3.213708e-01 6.792890e-01 4.072636e-01 1.727583e-01 9.433523e-01
#> [41] 8.809056e-05 3.316930e-01 3.605975e-02 1.727583e-01 2.060326e-01
#> [46] 3.741390e-03 7.063825e-01 3.010790e-01 7.198814e-01 5.493419e-01
#> [51] 1.348806e-01 4.407815e-01 7.473240e-01 7.026544e-04 6.003263e-01
#> [56] 1.574378e-02 7.026544e-04 4.642451e-01 3.605975e-02 1.495851e-01
#> [61] 2.519326e-01 7.611772e-01 9.021435e-01 5.123801e-01 1.973602e-01
#> [66] 9.237228e-03 8.460096e-01 3.849937e-01 1.936105e-02 2.688525e-02
#> [71] 9.433523e-01 1.888945e-01 6.265284e-02 6.134027e-01 8.735874e-02
#> [76] 1.495851e-01 9.714577e-01 2.238252e-01 5.873770e-01 2.615704e-01
#> [81] 5.000524e-01 2.422929e-01 5.369194e-01 3.421108e-01 4.642451e-01
#> [86] 6.792890e-01 5.123801e-01 8.735874e-02 1.421182e-01 9.021435e-01
#> [91] 7.026544e-04 4.642451e-01 7.198814e-01 9.021435e-01 8.739880e-01
#> [96] 2.615704e-01 7.486315e-02 2.238252e-01 6.134027e-01 3.127512e-02
#> [101] 3.741390e-03 4.072636e-01 6.134027e-01 4.407815e-01 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 145 127 86 181 66 117 105 36 111 180 52 77 179
#> 10.07 3.53 23.81 16.46 22.13 17.46 19.75 21.19 17.45 14.82 10.42 7.27 18.63
#> 149 52.1 153 117.1 92 188 190 133 175 164 81 90 36.1
#> 8.37 10.42 21.33 17.46 22.92 16.16 20.81 14.65 21.91 23.60 14.06 20.94 21.19
#> 32 79 139 61 85 81.1 175.1 187 85.1 106 123 188.1 170
#> 20.90 16.23 21.49 10.12 16.44 14.06 21.91 9.92 16.44 16.67 13.00 16.16 19.54
#> 91 24 171 194 170.1 179.1 86.1 154 111.1 56 180.1 128 100
#> 5.33 23.89 16.57 22.40 19.54 18.63 23.81 12.63 17.45 12.21 14.82 20.35 16.07
#> 49 78 13 129 78.1 26 194.1 158 134 159 25 167 97
#> 12.19 23.88 14.34 23.41 23.88 15.77 22.40 20.14 17.81 10.55 6.32 15.55 19.14
#> 168 149.1 5 92.1 113 91.1 55 139.1 81.2 36.2 158.1 127.1 8
#> 23.72 8.37 16.43 22.92 22.86 5.33 19.34 21.49 14.06 21.19 20.14 3.53 18.43
#> 96 110 125 88 18 130 26.1 123.1 167.1 36.3 150 25.1 78.2
#> 14.54 17.56 15.65 18.37 15.21 16.47 15.77 13.00 15.55 21.19 20.33 6.32 23.88
#> 26.2 56.1 25.2 70 110.1 153.1 8.1 81.3 169 86.2 188.2 81.4 100.1
#> 15.77 12.21 6.32 7.38 17.56 21.33 18.43 14.06 22.41 23.81 16.16 14.06 16.07
#> 174 135 47 173 162 146 3 47.1 122 87 33 176 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 82 122.1 165 186 65 19 126 71 74 83 193 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 35 44 191 53 47.2 11 64 147 1 11.1 53.1 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 118 94 3.1 48 141 156 178 191.1 33.2 34 126.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 193.2 200 64.1 38.1 94.1 135.1 35.1 46 144 84 200.1 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 173.1 176.1 152 144.1 178.1 20 31 3.2 146.1 71.2 44.1 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 20.1 104 54 142 102 94.2 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[53]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01049424 0.65230916 0.18321874
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.79326000 0.01193572 0.04568128
#> grade_iii, Cure model
#> 1.12477742
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 194 22.40 1 38 0 1
#> 92 22.92 1 47 0 1
#> 10 10.53 1 34 0 0
#> 90 20.94 1 50 0 1
#> 164 23.60 1 76 0 1
#> 66.1 22.13 1 53 0 0
#> 18 15.21 1 49 1 0
#> 55 19.34 1 69 0 1
#> 59 10.16 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 56 12.21 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 183 9.24 1 67 1 0
#> 189.1 10.51 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 107 11.18 1 54 1 0
#> 52 10.42 1 52 0 1
#> 77 7.27 1 67 0 1
#> 76 19.22 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 78 23.88 1 43 0 0
#> 188 16.16 1 46 0 1
#> 197 21.60 1 69 1 0
#> 78.1 23.88 1 43 0 0
#> 105 19.75 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 42 12.43 1 49 0 1
#> 108 18.29 1 39 0 1
#> 101 9.97 1 10 0 1
#> 105.1 19.75 1 60 0 0
#> 127 3.53 1 62 0 1
#> 32 20.90 1 37 1 0
#> 159 10.55 1 50 0 1
#> 69 23.23 1 25 0 1
#> 181 16.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 195.1 11.76 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 29 15.45 1 68 1 0
#> 26 15.77 1 49 0 1
#> 26.1 15.77 1 49 0 1
#> 111 17.45 1 47 0 1
#> 107.1 11.18 1 54 1 0
#> 10.2 10.53 1 34 0 0
#> 30 17.43 1 78 0 0
#> 110 17.56 1 65 0 1
#> 58 19.34 1 39 0 0
#> 59.2 10.16 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 101.2 9.97 1 10 0 1
#> 93 10.33 1 52 0 1
#> 187 9.92 1 39 1 0
#> 164.1 23.60 1 76 0 1
#> 158.1 20.14 1 74 1 0
#> 30.1 17.43 1 78 0 0
#> 107.2 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 42.1 12.43 1 49 0 1
#> 61 10.12 1 36 0 1
#> 150 20.33 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 108.1 18.29 1 39 0 1
#> 145 10.07 1 65 1 0
#> 41 18.02 1 40 1 0
#> 56.1 12.21 1 60 0 0
#> 57 14.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 77.1 7.27 1 67 0 1
#> 51 18.23 1 83 0 1
#> 32.1 20.90 1 37 1 0
#> 101.3 9.97 1 10 0 1
#> 187.2 9.92 1 39 1 0
#> 18.1 15.21 1 49 1 0
#> 51.1 18.23 1 83 0 1
#> 130.1 16.47 1 53 0 1
#> 55.1 19.34 1 69 0 1
#> 136 21.83 1 43 0 1
#> 99 21.19 1 38 0 1
#> 134 17.81 1 47 1 0
#> 14 12.89 1 21 0 0
#> 110.1 17.56 1 65 0 1
#> 97 19.14 1 65 0 1
#> 175.1 21.91 1 43 0 0
#> 180 14.82 1 37 0 0
#> 57.1 14.46 1 45 0 1
#> 117 17.46 1 26 0 1
#> 14.1 12.89 1 21 0 0
#> 30.2 17.43 1 78 0 0
#> 61.1 10.12 1 36 0 1
#> 106 16.67 1 49 1 0
#> 59.3 10.16 1 NA 1 0
#> 42.2 12.43 1 49 0 1
#> 36 21.19 1 48 0 1
#> 93.1 10.33 1 52 0 1
#> 170.1 19.54 1 43 0 1
#> 14.2 12.89 1 21 0 0
#> 125 15.65 1 67 1 0
#> 177 12.53 1 75 0 0
#> 155.1 13.08 1 26 0 0
#> 70 7.38 1 30 1 0
#> 10.3 10.53 1 34 0 0
#> 66.2 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 10.4 10.53 1 34 0 0
#> 194.1 22.40 1 38 0 1
#> 98 24.00 0 34 1 0
#> 118 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 31 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 174 24.00 0 49 1 0
#> 2 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 147 24.00 0 76 1 0
#> 33 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 17.1 24.00 0 38 0 1
#> 191.1 24.00 0 60 0 1
#> 21 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 62.1 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 126 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 21.1 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 119.1 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 28 24.00 0 67 1 0
#> 109.1 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 19.1 24.00 0 57 0 1
#> 87 24.00 0 27 0 0
#> 44 24.00 0 56 0 0
#> 94 24.00 0 51 0 1
#> 54 24.00 0 53 1 0
#> 17.2 24.00 0 38 0 1
#> 71 24.00 0 51 0 0
#> 196.1 24.00 0 19 0 0
#> 135.1 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 182 24.00 0 35 0 0
#> 67 24.00 0 25 0 0
#> 172 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 31.1 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 65.1 24.00 0 57 1 0
#> 191.2 24.00 0 60 0 1
#> 95 24.00 0 68 0 1
#> 120 24.00 0 68 0 1
#> 33.1 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 160.1 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 11 24.00 0 42 0 1
#> 196.2 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 17.3 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 67.1 24.00 0 25 0 0
#> 121.1 24.00 0 57 1 0
#> 46 24.00 0 71 0 0
#> 87.1 24.00 0 27 0 0
#> 54.1 24.00 0 53 1 0
#> 126.1 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 54.2 24.00 0 53 1 0
#> 142 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 118.1 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 95.1 24.00 0 68 0 1
#> 135.2 24.00 0 58 1 0
#> 21.2 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 137.1 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 119.2 24.00 0 17 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.793 NA NA NA
#> 2 age, Cure model 0.0119 NA NA NA
#> 3 grade_ii, Cure model 0.0457 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0105 NA NA NA
#> 2 grade_ii, Survival model 0.652 NA NA NA
#> 3 grade_iii, Survival model 0.183 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.79326 0.01194 0.04568 1.12478
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 245 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.79326000 0.01193572 0.04568128 1.12477742
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01049424 0.65230916 0.18321874
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.035538461 0.024905070 0.019411809 0.724092711 0.097848965 0.006122323
#> [7] 0.035538461 0.474839966 0.185864491 0.278516858 0.642337275 0.367298813
#> [13] 0.939484236 0.585192906 0.677628295 0.782600852 0.963619274 0.212017100
#> [19] 0.136694601 0.001273367 0.420271869 0.075012045 0.001273367 0.152422815
#> [25] 0.724092711 0.608022448 0.230628895 0.855734461 0.152422815 0.987785786
#> [31] 0.105959907 0.712289887 0.014310065 0.409504431 0.168948618 0.529513856
#> [37] 0.463822831 0.431111195 0.431111195 0.326965289 0.677628295 0.724092711
#> [43] 0.336901267 0.297754065 0.185864491 0.855734461 0.388390190 0.855734461
#> [49] 0.794725831 0.903677471 0.006122323 0.136694601 0.336901267 0.677628295
#> [55] 0.053465555 0.608022448 0.819014465 0.128702012 0.120901220 0.230628895
#> [61] 0.843431175 0.268724419 0.642337275 0.507486402 0.903677471 0.963619274
#> [67] 0.249314745 0.105959907 0.855734461 0.903677471 0.474839966 0.249314745
#> [73] 0.388390190 0.185864491 0.067429528 0.082648658 0.288163124 0.551762422
#> [79] 0.297754065 0.221246110 0.053465555 0.496471899 0.507486402 0.317109166
#> [85] 0.551762422 0.336901267 0.819014465 0.377866282 0.608022448 0.082648658
#> [91] 0.794725831 0.168948618 0.551762422 0.452821245 0.596548178 0.529513856
#> [97] 0.951582468 0.724092711 0.035538461 0.665816815 0.724092711 0.024905070
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 66 194 92 10 90 164 66.1 18 55 40 56 23 183
#> 22.13 22.40 22.92 10.53 20.94 23.60 22.13 15.21 19.34 18.00 12.21 16.92 9.24
#> 140 107 52 77 76 158 78 188 197 78.1 105 10.1 42
#> 12.68 11.18 10.42 7.27 19.22 20.14 23.88 16.16 21.60 23.88 19.75 10.53 12.43
#> 108 101 105.1 127 32 159 69 181 170 155 29 26 26.1
#> 18.29 9.97 19.75 3.53 20.90 10.55 23.23 16.46 19.54 13.08 15.45 15.77 15.77
#> 111 107.1 10.2 30 110 58 101.1 130 101.2 93 187 164.1 158.1
#> 17.45 11.18 10.53 17.43 17.56 19.34 9.97 16.47 9.97 10.33 9.92 23.60 20.14
#> 30.1 107.2 175 42.1 61 150 128 108.1 145 41 56.1 57 187.1
#> 17.43 11.18 21.91 12.43 10.12 20.33 20.35 18.29 10.07 18.02 12.21 14.46 9.92
#> 77.1 51 32.1 101.3 187.2 18.1 51.1 130.1 55.1 136 99 134 14
#> 7.27 18.23 20.90 9.97 9.92 15.21 18.23 16.47 19.34 21.83 21.19 17.81 12.89
#> 110.1 97 175.1 180 57.1 117 14.1 30.2 61.1 106 42.2 36 93.1
#> 17.56 19.14 21.91 14.82 14.46 17.46 12.89 17.43 10.12 16.67 12.43 21.19 10.33
#> 170.1 14.2 125 177 155.1 70 10.3 66.2 49 10.4 194.1 98 118
#> 19.54 12.89 15.65 12.53 13.08 7.38 10.53 22.13 12.19 10.53 22.40 24.00 24.00
#> 109 112 119 31 17 191 174 2 165 147 33 178 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 191.1 21 62 132 137 62.1 19 126 53 21.1 34 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 144 28 109.1 135 65 19.1 87 44 94 54 17.2 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 135.1 138 98.1 182 67 172 160 22 83 31.1 75 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.2 95 120 33.1 148 160.1 1 11 196.2 121 17.3 200 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 46 87.1 54.1 126.1 12 54.2 142 72 118.1 161 95.1 135.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.2 151 137.1 176 80 119.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[54]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002123277 1.230185774 0.556347628
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.58549294 0.01095971 -0.23225643
#> grade_iii, Cure model
#> 0.94393742
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 57 14.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 110 17.56 1 65 0 1
#> 117 17.46 1 26 0 1
#> 18 15.21 1 49 1 0
#> 86 23.81 1 58 0 1
#> 127 3.53 1 62 0 1
#> 4 17.64 1 NA 0 1
#> 124 9.73 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 192 16.44 1 31 1 0
#> 155 13.08 1 26 0 0
#> 179 18.63 1 42 0 0
#> 78 23.88 1 43 0 0
#> 194 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 158 20.14 1 74 1 0
#> 113 22.86 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 29 15.45 1 68 1 0
#> 18.1 15.21 1 49 1 0
#> 99 21.19 1 38 0 1
#> 43 12.10 1 61 0 1
#> 91 5.33 1 61 0 1
#> 155.1 13.08 1 26 0 0
#> 77.1 7.27 1 67 0 1
#> 110.1 17.56 1 65 0 1
#> 164 23.60 1 76 0 1
#> 111 17.45 1 47 0 1
#> 100 16.07 1 60 0 0
#> 10 10.53 1 34 0 0
#> 5 16.43 1 51 0 1
#> 89 11.44 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 60 13.15 1 38 1 0
#> 180 14.82 1 37 0 0
#> 107 11.18 1 54 1 0
#> 18.2 15.21 1 49 1 0
#> 92 22.92 1 47 0 1
#> 105 19.75 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 91.1 5.33 1 61 0 1
#> 130 16.47 1 53 0 1
#> 167 15.55 1 56 1 0
#> 49 12.19 1 48 1 0
#> 90.1 20.94 1 50 0 1
#> 113.1 22.86 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 76 19.22 1 54 0 1
#> 181 16.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 61 10.12 1 36 0 1
#> 86.1 23.81 1 58 0 1
#> 39 15.59 1 37 0 1
#> 194.1 22.40 1 38 0 1
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 91.2 5.33 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 164.1 23.60 1 76 0 1
#> 4.1 17.64 1 NA 0 1
#> 70 7.38 1 30 1 0
#> 167.1 15.55 1 56 1 0
#> 183 9.24 1 67 1 0
#> 51 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 43.1 12.10 1 61 0 1
#> 124.1 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 8.1 18.43 1 32 0 0
#> 39.1 15.59 1 37 0 1
#> 108.1 18.29 1 39 0 1
#> 50 10.02 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 145 10.07 1 65 1 0
#> 124.2 9.73 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 194.2 22.40 1 38 0 1
#> 167.2 15.55 1 56 1 0
#> 40 18.00 1 28 1 0
#> 100.1 16.07 1 60 0 0
#> 168 23.72 1 70 0 0
#> 55 19.34 1 69 0 1
#> 57.1 14.46 1 45 0 1
#> 24.1 23.89 1 38 0 0
#> 23 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 89.1 11.44 1 NA 0 0
#> 57.2 14.46 1 45 0 1
#> 57.3 14.46 1 45 0 1
#> 78.1 23.88 1 43 0 0
#> 123 13.00 1 44 1 0
#> 177.1 12.53 1 75 0 0
#> 58 19.34 1 39 0 0
#> 140 12.68 1 59 1 0
#> 169 22.41 1 46 0 0
#> 194.3 22.40 1 38 0 1
#> 45 17.42 1 54 0 1
#> 149.1 8.37 1 33 1 0
#> 192.1 16.44 1 31 1 0
#> 58.1 19.34 1 39 0 0
#> 24.2 23.89 1 38 0 0
#> 140.1 12.68 1 59 1 0
#> 96 14.54 1 33 0 1
#> 183.1 9.24 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 169.1 22.41 1 46 0 0
#> 23.1 16.92 1 61 0 0
#> 197 21.60 1 69 1 0
#> 30 17.43 1 78 0 0
#> 75 24.00 0 21 1 0
#> 12 24.00 0 63 0 0
#> 144 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 48 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 73 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 131 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 120 24.00 0 68 0 1
#> 147.1 24.00 0 76 1 0
#> 67 24.00 0 25 0 0
#> 38 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 122 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 163 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 160 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 122.1 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 11 24.00 0 42 0 1
#> 65 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 118 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 104 24.00 0 50 1 0
#> 120.1 24.00 0 68 0 1
#> 160.1 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 53 24.00 0 32 0 1
#> 83 24.00 0 6 0 0
#> 22 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 48.1 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 82.1 24.00 0 34 0 0
#> 126 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 46.1 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 138.1 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 138.2 24.00 0 44 1 0
#> 174.2 24.00 0 49 1 0
#> 46.2 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 22.1 24.00 0 52 1 0
#> 126.1 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 20 24.00 0 46 1 0
#> 80 24.00 0 41 0 0
#> 120.2 24.00 0 68 0 1
#> 31 24.00 0 36 0 1
#> 75.1 24.00 0 21 1 0
#> 20.1 24.00 0 46 1 0
#> 196.2 24.00 0 19 0 0
#> 34.1 24.00 0 36 0 0
#> 148 24.00 0 61 1 0
#> 152.1 24.00 0 36 0 1
#> 174.3 24.00 0 49 1 0
#> 160.2 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 11.1 24.00 0 42 0 1
#> 163.1 24.00 0 66 0 0
#> 22.2 24.00 0 52 1 0
#> 116.1 24.00 0 58 0 1
#> 65.2 24.00 0 57 1 0
#> 152.2 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.585 NA NA NA
#> 2 age, Cure model 0.0110 NA NA NA
#> 3 grade_ii, Cure model -0.232 NA NA NA
#> 4 grade_iii, Cure model 0.944 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00212 NA NA NA
#> 2 grade_ii, Survival model 1.23 NA NA NA
#> 3 grade_iii, Survival model 0.556 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.58549 0.01096 -0.23226 0.94394
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 247.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.58549294 0.01095971 -0.23225643 0.94393742
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002123277 1.230185774 0.556347628
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8232818 0.5971691 0.6318197 0.6480692 0.7937227 0.1777272 0.9955922
#> [8] 0.9734154 0.7183731 0.8573866 0.5700400 0.1230787 0.3604201 0.4750363
#> [15] 0.4954036 0.2943926 0.9207428 0.7873758 0.7937227 0.4277157 0.9056158
#> [22] 0.9823695 0.8573866 0.9734154 0.6318197 0.2417868 0.6561594 0.7398814
#> [29] 0.9257167 0.7327325 0.4519573 0.8517734 0.8114327 0.9157435 0.7937227
#> [36] 0.2771577 0.5050897 0.6561594 0.9823695 0.7030522 0.7680315 0.9004810
#> [43] 0.4519573 0.2943926 0.9257167 0.5519509 0.7107505 0.9597348 0.9405747
#> [50] 0.1777272 0.7540729 0.3604201 0.4277157 0.8952632 0.9823695 0.4750363
#> [57] 0.2417868 0.9688858 0.7680315 0.9503448 0.6147203 0.5791439 0.9056158
#> [64] 0.8460581 0.5050897 0.5791439 0.7540729 0.5971691 0.0489275 0.9454967
#> [71] 0.9356298 0.3604201 0.7680315 0.6234242 0.7398814 0.2199199 0.5241778
#> [78] 0.8232818 0.0489275 0.6875793 0.8846820 0.8232818 0.8232818 0.1230787
#> [85] 0.8685681 0.8846820 0.5241778 0.8740789 0.3275754 0.3604201 0.6797744
#> [92] 0.9597348 0.7183731 0.5241778 0.0489275 0.8740789 0.8173760 0.9503448
#> [99] 0.5519509 0.3275754 0.6875793 0.4147385 0.6718829 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 57 108 110 117 18 86 127 77 192 155 179 78 194
#> 14.46 18.29 17.56 17.46 15.21 23.81 3.53 7.27 16.44 13.08 18.63 23.88 22.40
#> 190 158 113 159 29 18.1 99 43 91 155.1 77.1 110.1 164
#> 20.81 20.14 22.86 10.55 15.45 15.21 21.19 12.10 5.33 13.08 7.27 17.56 23.60
#> 111 100 10 5 90 60 180 107 18.2 92 105 111.1 91.1
#> 17.45 16.07 10.53 16.43 20.94 13.15 14.82 11.18 15.21 22.92 19.75 17.45 5.33
#> 130 167 49 90.1 113.1 10.1 76 181 149 61 86.1 39 194.1
#> 16.47 15.55 12.19 20.94 22.86 10.53 19.22 16.46 8.37 10.12 23.81 15.59 22.40
#> 36 37 91.2 190.1 164.1 70 167.1 183 51 8 43.1 13 105.1
#> 21.19 12.52 5.33 20.81 23.60 7.38 15.55 9.24 18.23 18.43 12.10 14.34 19.75
#> 8.1 39.1 108.1 24 145 52 194.2 167.2 40 100.1 168 55 57.1
#> 18.43 15.59 18.29 23.89 10.07 10.42 22.40 15.55 18.00 16.07 23.72 19.34 14.46
#> 24.1 23 177 57.2 57.3 78.1 123 177.1 58 140 169 194.3 45
#> 23.89 16.92 12.53 14.46 14.46 23.88 13.00 12.53 19.34 12.68 22.41 22.40 17.42
#> 149.1 192.1 58.1 24.2 140.1 96 183.1 76.1 169.1 23.1 197 30 75
#> 8.37 16.44 19.34 23.89 12.68 14.54 9.24 19.22 22.41 16.92 21.60 17.43 24.00
#> 12 144 82 48 147 102 46 162 27 131 151 120 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 38 152 21 174 122 84 163 191 160 174.1 138 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 9 116 11 65 142 118 156 185 176 104 120.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 196 53 83 22 33 112 48.1 196.1 82.1 126 47 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 198 138.1 65.1 62 34 138.2 174.2 46.2 98 22.1 126.1 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 80 120.2 31 75.1 20.1 196.2 34.1 148 152.1 174.3 160.2 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 11.1 163.1 22.2 116.1 65.2 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[55]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006624913 0.154259433 0.229387306
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.235213988 0.004188793 -0.198266793
#> grade_iii, Cure model
#> 0.814774442
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 125 15.65 1 67 1 0
#> 57 14.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 56 12.21 1 60 0 0
#> 97 19.14 1 65 0 1
#> 96 14.54 1 33 0 1
#> 15 22.68 1 48 0 0
#> 14 12.89 1 21 0 0
#> 110 17.56 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 180 14.82 1 37 0 0
#> 139 21.49 1 63 1 0
#> 66 22.13 1 53 0 0
#> 128 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 5 16.43 1 51 0 1
#> 105 19.75 1 60 0 0
#> 16 8.71 1 71 0 1
#> 25 6.32 1 34 1 0
#> 58 19.34 1 39 0 0
#> 199 19.81 1 NA 0 1
#> 188 16.16 1 46 0 1
#> 32 20.90 1 37 1 0
#> 99 21.19 1 38 0 1
#> 140 12.68 1 59 1 0
#> 61 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 170 19.54 1 43 0 1
#> 184 17.77 1 38 0 0
#> 157 15.10 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 113 22.86 1 34 0 0
#> 63 22.77 1 31 1 0
#> 55 19.34 1 69 0 1
#> 130 16.47 1 53 0 1
#> 199.1 19.81 1 NA 0 1
#> 170.1 19.54 1 43 0 1
#> 16.1 8.71 1 71 0 1
#> 136 21.83 1 43 0 1
#> 184.1 17.77 1 38 0 0
#> 150 20.33 1 48 0 0
#> 169 22.41 1 46 0 0
#> 40.1 18.00 1 28 1 0
#> 107 11.18 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 10 10.53 1 34 0 0
#> 199.2 19.81 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 125.1 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 190 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 108 18.29 1 39 0 1
#> 77.1 7.27 1 67 0 1
#> 184.2 17.77 1 38 0 0
#> 86 23.81 1 58 0 1
#> 32.1 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 66.1 22.13 1 53 0 0
#> 43 12.10 1 61 0 1
#> 195.1 11.76 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 81 14.06 1 34 0 0
#> 114.1 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 92 22.92 1 47 0 1
#> 100.1 16.07 1 60 0 0
#> 29 15.45 1 68 1 0
#> 14.2 12.89 1 21 0 0
#> 195.2 11.76 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 194 22.40 1 38 0 1
#> 63.1 22.77 1 31 1 0
#> 114.2 13.68 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 150.1 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 125.2 15.65 1 67 1 0
#> 66.2 22.13 1 53 0 0
#> 100.2 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 157.1 15.10 1 47 0 0
#> 55.1 19.34 1 69 0 1
#> 111 17.45 1 47 0 1
#> 188.1 16.16 1 46 0 1
#> 42 12.43 1 49 0 1
#> 10.1 10.53 1 34 0 0
#> 197.1 21.60 1 69 1 0
#> 40.2 18.00 1 28 1 0
#> 100.3 16.07 1 60 0 0
#> 14.3 12.89 1 21 0 0
#> 194.1 22.40 1 38 0 1
#> 133 14.65 1 57 0 0
#> 159.1 10.55 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 25.1 6.32 1 34 1 0
#> 157.2 15.10 1 47 0 0
#> 91 5.33 1 61 0 1
#> 123 13.00 1 44 1 0
#> 145 10.07 1 65 1 0
#> 117.1 17.46 1 26 0 1
#> 128.1 20.35 1 35 0 1
#> 78.1 23.88 1 43 0 0
#> 81.1 14.06 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 189.1 10.51 1 NA 1 0
#> 132 24.00 0 55 0 0
#> 143 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 119 24.00 0 17 0 0
#> 80 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 119.1 24.00 0 17 0 0
#> 47 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 119.2 24.00 0 17 0 0
#> 28 24.00 0 67 1 0
#> 84 24.00 0 39 0 1
#> 121.1 24.00 0 57 1 0
#> 161 24.00 0 45 0 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#> 2 24.00 0 9 0 0
#> 186 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 47.2 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 48 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 71 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 152 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 200 24.00 0 64 0 0
#> 152.1 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 53 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 65.1 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 74 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 21 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 160.2 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 74.1 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 126 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 172 24.00 0 41 0 0
#> 132.1 24.00 0 55 0 0
#> 165.2 24.00 0 47 0 0
#> 137 24.00 0 45 1 0
#> 132.2 24.00 0 55 0 0
#> 162 24.00 0 51 0 0
#> 27.1 24.00 0 63 1 0
#> 65.2 24.00 0 57 1 0
#> 71.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 27.2 24.00 0 63 1 0
#> 83.1 24.00 0 6 0 0
#> 46 24.00 0 71 0 0
#> 121.2 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 151 24.00 0 42 0 0
#> 75 24.00 0 21 1 0
#> 186.1 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 33.1 24.00 0 53 0 0
#> 126.1 24.00 0 48 0 0
#> 12.1 24.00 0 63 0 0
#> 34.2 24.00 0 36 0 0
#> 120.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.235 NA NA NA
#> 2 age, Cure model 0.00419 NA NA NA
#> 3 grade_ii, Cure model -0.198 NA NA NA
#> 4 grade_iii, Cure model 0.815 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00662 NA NA NA
#> 2 grade_ii, Survival model 0.154 NA NA NA
#> 3 grade_iii, Survival model 0.229 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.235214 0.004189 -0.198267 0.814774
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 249.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.235213988 0.004188793 -0.198266793 0.814774442
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006624913 0.154259433 0.229387306
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86463389 0.71020124 0.80000977 0.55213086 0.87882561 0.51563396
#> [7] 0.79265387 0.18885587 0.82904463 0.60430162 0.77783241 0.33981162
#> [13] 0.26403710 0.39669121 0.31580956 0.64669440 0.43872744 0.95427647
#> [19] 0.98055522 0.46911463 0.66317912 0.36335049 0.35170270 0.85747876
#> [25] 0.93401347 0.89983108 0.44914211 0.57838450 0.75570602 0.92719832
#> [31] 0.13616104 0.15564771 0.46911463 0.63833570 0.44914211 0.95427647
#> [37] 0.30271662 0.57838450 0.41790702 0.22003037 0.55213086 0.89286998
#> [43] 0.52488017 0.91354059 0.94754601 0.71020124 0.74817606 0.38558481
#> [49] 0.96750154 0.54305989 0.96750154 0.57838450 0.09287449 0.36335049
#> [55] 0.50623012 0.26403710 0.88587240 0.04377829 0.80731898 0.67921446
#> [61] 0.82904463 0.11595012 0.67921446 0.74059927 0.82904463 0.18885587
#> [67] 0.23580016 0.15564771 0.73295752 0.52488017 0.41790702 0.65497144
#> [73] 0.71020124 0.26403710 0.67921446 0.61294993 0.75570602 0.46911463
#> [79] 0.62988997 0.66317912 0.87175113 0.91354059 0.31580956 0.55213086
#> [85] 0.67921446 0.82904463 0.23580016 0.78525918 0.89983108 0.98055522
#> [91] 0.75570602 0.99352918 0.82180528 0.94079908 0.61294993 0.39669121
#> [97] 0.04377829 0.80731898 0.46911463 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 177 125 57 40 56 97 96 15 14 110 180 139 66
#> 12.53 15.65 14.46 18.00 12.21 19.14 14.54 22.68 12.89 17.56 14.82 21.49 22.13
#> 128 197 5 105 16 25 58 188 32 99 140 61 159
#> 20.35 21.60 16.43 19.75 8.71 6.32 19.34 16.16 20.90 21.19 12.68 10.12 10.55
#> 170 184 157 52 113 63 55 130 170.1 16.1 136 184.1 150
#> 19.54 17.77 15.10 10.42 22.86 22.77 19.34 16.47 19.54 8.71 21.83 17.77 20.33
#> 169 40.1 107 8 10 101 125.1 18 190 77 108 77.1 184.2
#> 22.41 18.00 11.18 18.43 10.53 9.97 15.65 15.21 20.81 7.27 18.29 7.27 17.77
#> 86 32.1 76 66.1 43 78 81 100 14.1 92 100.1 29 14.2
#> 23.81 20.90 19.22 22.13 12.10 23.88 14.06 16.07 12.89 22.92 16.07 15.45 12.89
#> 15.1 194 63.1 6 8.1 150.1 79 125.2 66.2 100.2 117 157.1 55.1
#> 22.68 22.40 22.77 15.64 18.43 20.33 16.23 15.65 22.13 16.07 17.46 15.10 19.34
#> 111 188.1 42 10.1 197.1 40.2 100.3 14.3 194.1 133 159.1 25.1 157.2
#> 17.45 16.16 12.43 10.53 21.60 18.00 16.07 12.89 22.40 14.65 10.55 6.32 15.10
#> 91 123 145 117.1 128.1 78.1 81.1 58.1 132 143 94 119 80
#> 5.33 13.00 10.07 17.46 20.35 23.88 14.06 19.34 24.00 24.00 24.00 24.00 24.00
#> 165 131 82 119.1 47 121 47.1 31 27 119.2 28 84 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 34 34.1 65 2 186 9 47.2 72 48 112 71 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 12 200 152.1 64 53 122 22 135 142 141 87 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 48.1 72.1 74 165.1 21 83 138 160 160.1 163 160.2 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 74.1 54 126 95 147 172 132.1 165.2 137 132.2 162 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 71.1 3 27.2 83.1 46 121.2 98 151 75 186.1 102 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.1 12.1 34.2 120.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[56]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007964796 0.493175935 0.558619531
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.02999860 0.01919188 0.22796488
#> grade_iii, Cure model
#> 0.91783480
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 139 21.49 1 63 1 0
#> 24 23.89 1 38 0 0
#> 69 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 133 14.65 1 57 0 0
#> 108 18.29 1 39 0 1
#> 90 20.94 1 50 0 1
#> 101 9.97 1 10 0 1
#> 61 10.12 1 36 0 1
#> 49 12.19 1 48 1 0
#> 154 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 189 10.51 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 85 16.44 1 36 0 0
#> 77 7.27 1 67 0 1
#> 16 8.71 1 71 0 1
#> 88.1 18.37 1 47 0 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 133.1 14.65 1 57 0 0
#> 8 18.43 1 32 0 0
#> 169 22.41 1 46 0 0
#> 157 15.10 1 47 0 0
#> 91 5.33 1 61 0 1
#> 149 8.37 1 33 1 0
#> 89 11.44 1 NA 0 0
#> 39 15.59 1 37 0 1
#> 13 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 166 19.98 1 48 0 0
#> 29 15.45 1 68 1 0
#> 127 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 86 23.81 1 58 0 1
#> 159 10.55 1 50 0 1
#> 37 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 139.1 21.49 1 63 1 0
#> 77.1 7.27 1 67 0 1
#> 188 16.16 1 46 0 1
#> 129 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 130 16.47 1 53 0 1
#> 77.2 7.27 1 67 0 1
#> 42 12.43 1 49 0 1
#> 93 10.33 1 52 0 1
#> 159.1 10.55 1 50 0 1
#> 69.1 23.23 1 25 0 1
#> 8.1 18.43 1 32 0 0
#> 56 12.21 1 60 0 0
#> 77.3 7.27 1 67 0 1
#> 107 11.18 1 54 1 0
#> 63 22.77 1 31 1 0
#> 49.1 12.19 1 48 1 0
#> 158 20.14 1 74 1 0
#> 100 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 195 11.76 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 195.1 11.76 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 190 20.81 1 42 1 0
#> 187 9.92 1 39 1 0
#> 37.1 12.52 1 57 1 0
#> 194 22.40 1 38 0 1
#> 15 22.68 1 48 0 0
#> 181 16.46 1 45 0 1
#> 61.1 10.12 1 36 0 1
#> 36 21.19 1 48 0 1
#> 24.1 23.89 1 38 0 0
#> 85.1 16.44 1 36 0 0
#> 58 19.34 1 39 0 0
#> 105 19.75 1 60 0 0
#> 159.2 10.55 1 50 0 1
#> 37.2 12.52 1 57 1 0
#> 78.1 23.88 1 43 0 0
#> 37.3 12.52 1 57 1 0
#> 57 14.46 1 45 0 1
#> 158.1 20.14 1 74 1 0
#> 43 12.10 1 61 0 1
#> 140 12.68 1 59 1 0
#> 24.2 23.89 1 38 0 0
#> 188.1 16.16 1 46 0 1
#> 166.1 19.98 1 48 0 0
#> 190.1 20.81 1 42 1 0
#> 37.4 12.52 1 57 1 0
#> 99.1 21.19 1 38 0 1
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 180.1 14.82 1 37 0 0
#> 69.2 23.23 1 25 0 1
#> 101.1 9.97 1 10 0 1
#> 77.4 7.27 1 67 0 1
#> 10 10.53 1 34 0 0
#> 134 17.81 1 47 1 0
#> 97.1 19.14 1 65 0 1
#> 79.1 16.23 1 54 1 0
#> 18 15.21 1 49 1 0
#> 16.1 8.71 1 71 0 1
#> 93.1 10.33 1 52 0 1
#> 14 12.89 1 21 0 0
#> 170 19.54 1 43 0 1
#> 18.1 15.21 1 49 1 0
#> 106 16.67 1 49 1 0
#> 108.1 18.29 1 39 0 1
#> 39.1 15.59 1 37 0 1
#> 41 18.02 1 40 1 0
#> 180.2 14.82 1 37 0 0
#> 156 24.00 0 50 1 0
#> 198 24.00 0 66 0 1
#> 71 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 71.1 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 87 24.00 0 27 0 0
#> 109 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 172.1 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 2.1 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#> 17 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 1.1 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 196 24.00 0 19 0 0
#> 116 24.00 0 58 0 1
#> 118 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 147 24.00 0 76 1 0
#> 142.1 24.00 0 53 0 0
#> 198.1 24.00 0 66 0 1
#> 12 24.00 0 63 0 0
#> 83 24.00 0 6 0 0
#> 196.1 24.00 0 19 0 0
#> 162 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 185 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 119.1 24.00 0 17 0 0
#> 95 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 3 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 196.2 24.00 0 19 0 0
#> 17.1 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 102 24.00 0 49 0 0
#> 174.1 24.00 0 49 1 0
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 9.1 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 186 24.00 0 45 1 0
#> 2.2 24.00 0 9 0 0
#> 116.1 24.00 0 58 0 1
#> 82.2 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 83.1 24.00 0 6 0 0
#> 19 24.00 0 57 0 1
#> 174.2 24.00 0 49 1 0
#> 115.1 24.00 0 NA 1 0
#> 174.3 24.00 0 49 1 0
#> 83.2 24.00 0 6 0 0
#> 87.1 24.00 0 27 0 0
#> 19.1 24.00 0 57 0 1
#> 137 24.00 0 45 1 0
#> 95.1 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 65 24.00 0 57 1 0
#> 94.1 24.00 0 51 0 1
#> 196.3 24.00 0 19 0 0
#> 27.1 24.00 0 63 1 0
#> 71.2 24.00 0 51 0 0
#> 87.2 24.00 0 27 0 0
#> 3.1 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 94.2 24.00 0 51 0 1
#> 74.1 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 141 24.00 0 44 1 0
#> 198.2 24.00 0 66 0 1
#> 46 24.00 0 71 0 0
#> 185.1 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.03 NA NA NA
#> 2 age, Cure model 0.0192 NA NA NA
#> 3 grade_ii, Cure model 0.228 NA NA NA
#> 4 grade_iii, Cure model 0.918 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00796 NA NA NA
#> 2 grade_ii, Survival model 0.493 NA NA NA
#> 3 grade_iii, Survival model 0.559 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03000 0.01919 0.22796 0.91783
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.4
#> Residual Deviance: 253 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.02999860 0.01919188 0.22796488 0.91783480
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007964796 0.493175935 0.558619531
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4089870 0.0853214 0.3057057 0.6070090 0.8053904 0.6224021 0.4763715
#> [8] 0.9446786 0.9310702 0.8836540 0.8433834 0.6588192 0.8272632 0.4452236
#> [15] 0.7182553 0.5757444 0.7055607 0.9711367 0.9580707 0.6070090 0.4333737
#> [22] 0.5674012 0.8053904 0.5914366 0.3806851 0.7832059 0.9917719 0.9667896
#> [29] 0.7486918 0.8218589 0.1786224 0.5237971 0.7662544 0.9959018 0.6372854
#> [36] 0.2389101 0.9031344 0.8486868 0.7604318 0.4089870 0.9711367 0.7306183
#> [43] 0.2864275 0.2649900 0.6926419 0.9711367 0.8736583 0.9218602 0.9031344
#> [50] 0.3057057 0.5914366 0.8786649 0.9711367 0.8983119 0.3509129 0.8836540
#> [57] 0.5058756 0.7426709 0.6657478 0.9401606 0.6793351 0.4866227 0.9536169
#> [64] 0.8486868 0.3951820 0.3659399 0.6991461 0.9310702 0.4452236 0.0853214
#> [71] 0.7055607 0.5588458 0.5414377 0.9031344 0.8486868 0.1786224 0.8486868
#> [78] 0.8163940 0.5058756 0.8934498 0.8380492 0.0853214 0.7306183 0.5237971
#> [85] 0.4866227 0.8486868 0.4452236 0.6725944 0.7888119 0.7888119 0.3057057
#> [92] 0.9446786 0.9711367 0.9171663 0.6517469 0.5757444 0.7182553 0.7719977
#> [99] 0.9580707 0.9218602 0.8326594 0.5502424 0.7719977 0.6860343 0.6224021
#> [106] 0.7486918 0.6445669 0.7888119 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 139 24 69 88 133 108 90 101 61 49 154 110 155
#> 21.49 23.89 23.23 18.37 14.65 18.29 20.94 9.97 10.12 12.19 12.63 17.56 13.08
#> 99 79 97 85 77 16 88.1 153 76 133.1 8 169 157
#> 21.19 16.23 19.14 16.44 7.27 8.71 18.37 21.33 19.22 14.65 18.43 22.41 15.10
#> 91 149 39 13 78 166 29 127 51 86 159 37 167
#> 5.33 8.37 15.59 14.34 23.88 19.98 15.45 3.53 18.23 23.81 10.55 12.52 15.55
#> 139.1 77.1 188 129 164 130 77.2 42 93 159.1 69.1 8.1 56
#> 21.49 7.27 16.16 23.41 23.60 16.47 7.27 12.43 10.33 10.55 23.23 18.43 12.21
#> 77.3 107 63 49.1 158 100 117 145 23 190 187 37.1 194
#> 7.27 11.18 22.77 12.19 20.14 16.07 17.46 10.07 16.92 20.81 9.92 12.52 22.40
#> 15 181 61.1 36 24.1 85.1 58 105 159.2 37.2 78.1 37.3 57
#> 22.68 16.46 10.12 21.19 23.89 16.44 19.34 19.75 10.55 12.52 23.88 12.52 14.46
#> 158.1 43 140 24.2 188.1 166.1 190.1 37.4 99.1 111 180 180.1 69.2
#> 20.14 12.10 12.68 23.89 16.16 19.98 20.81 12.52 21.19 17.45 14.82 14.82 23.23
#> 101.1 77.4 10 134 97.1 79.1 18 16.1 93.1 14 170 18.1 106
#> 9.97 7.27 10.53 17.81 19.14 16.23 15.21 8.71 10.33 12.89 19.54 15.21 16.67
#> 108.1 39.1 41 180.2 156 198 71 126 163 2 172 71.1 176
#> 18.29 15.59 18.02 14.82 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 31 1 87 109 94 172.1 131 104 2.1 82 17 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 119 196 116 118 182 147 142.1 198.1 12 83 196.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 185 162.1 38 9 138 27 119.1 95 174 3 28 196.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 7 102 174.1 74 9.1 82.1 186 2.2 116.1 82.2 165 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 174.2 174.3 83.2 87.1 19.1 137 95.1 84 65 94.1 196.3 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 87.2 3.1 53 94.2 74.1 146 141 198.2 46 185.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[57]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01342448 0.84470089 0.47535330
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.059437697 -0.003339332 -0.111654447
#> grade_iii, Cure model
#> 1.094841878
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 181 16.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 79 16.23 1 54 1 0
#> 168 23.72 1 70 0 0
#> 49 12.19 1 48 1 0
#> 175 21.91 1 43 0 0
#> 55.1 19.34 1 69 0 1
#> 192 16.44 1 31 1 0
#> 79.1 16.23 1 54 1 0
#> 70 7.38 1 30 1 0
#> 194 22.40 1 38 0 1
#> 167 15.55 1 56 1 0
#> 26 15.77 1 49 0 1
#> 155 13.08 1 26 0 0
#> 90 20.94 1 50 0 1
#> 57 14.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 37 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 106 16.67 1 49 1 0
#> 88 18.37 1 47 0 0
#> 187 9.92 1 39 1 0
#> 90.2 20.94 1 50 0 1
#> 101 9.97 1 10 0 1
#> 194.1 22.40 1 38 0 1
#> 6 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 166 19.98 1 48 0 0
#> 130 16.47 1 53 0 1
#> 167.1 15.55 1 56 1 0
#> 85 16.44 1 36 0 0
#> 57.1 14.46 1 45 0 1
#> 101.1 9.97 1 10 0 1
#> 197 21.60 1 69 1 0
#> 190 20.81 1 42 1 0
#> 167.2 15.55 1 56 1 0
#> 66 22.13 1 53 0 0
#> 57.2 14.46 1 45 0 1
#> 15.1 22.68 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 16 8.71 1 71 0 1
#> 37.1 12.52 1 57 1 0
#> 127.1 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 36 21.19 1 48 0 1
#> 16.1 8.71 1 71 0 1
#> 100 16.07 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 190.1 20.81 1 42 1 0
#> 96 14.54 1 33 0 1
#> 150 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 123 13.00 1 44 1 0
#> 108.1 18.29 1 39 0 1
#> 90.3 20.94 1 50 0 1
#> 70.1 7.38 1 30 1 0
#> 197.1 21.60 1 69 1 0
#> 96.1 14.54 1 33 0 1
#> 157 15.10 1 47 0 0
#> 113 22.86 1 34 0 0
#> 14 12.89 1 21 0 0
#> 36.1 21.19 1 48 0 1
#> 88.1 18.37 1 47 0 0
#> 61 10.12 1 36 0 1
#> 78 23.88 1 43 0 0
#> 139 21.49 1 63 1 0
#> 100.1 16.07 1 60 0 0
#> 5 16.43 1 51 0 1
#> 134 17.81 1 47 1 0
#> 69 23.23 1 25 0 1
#> 114 13.68 1 NA 0 0
#> 171 16.57 1 41 0 1
#> 127.2 3.53 1 62 0 1
#> 150.1 20.33 1 48 0 0
#> 70.2 7.38 1 30 1 0
#> 175.1 21.91 1 43 0 0
#> 110.1 17.56 1 65 0 1
#> 169 22.41 1 46 0 0
#> 4 17.64 1 NA 0 1
#> 61.1 10.12 1 36 0 1
#> 55.2 19.34 1 69 0 1
#> 130.1 16.47 1 53 0 1
#> 149 8.37 1 33 1 0
#> 68 20.62 1 44 0 0
#> 192.1 16.44 1 31 1 0
#> 101.2 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 175.2 21.91 1 43 0 0
#> 154 12.63 1 20 1 0
#> 70.3 7.38 1 30 1 0
#> 6.1 15.64 1 39 0 0
#> 164 23.60 1 76 0 1
#> 114.1 13.68 1 NA 0 0
#> 155.1 13.08 1 26 0 0
#> 8 18.43 1 32 0 0
#> 66.1 22.13 1 53 0 0
#> 175.3 21.91 1 43 0 0
#> 89.1 11.44 1 NA 0 0
#> 23 16.92 1 61 0 0
#> 56 12.21 1 60 0 0
#> 63 22.77 1 31 1 0
#> 86 23.81 1 58 0 1
#> 89.2 11.44 1 NA 0 0
#> 13 14.34 1 54 0 1
#> 134.1 17.81 1 47 1 0
#> 183 9.24 1 67 1 0
#> 139.1 21.49 1 63 1 0
#> 11 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 198 24.00 0 66 0 1
#> 138 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 65.1 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 94 24.00 0 51 0 1
#> 143 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 121 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 118 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 118.1 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 138.1 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 193 24.00 0 45 0 1
#> 148.1 24.00 0 61 1 0
#> 141.1 24.00 0 44 1 0
#> 148.2 24.00 0 61 1 0
#> 120 24.00 0 68 0 1
#> 109.1 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 156 24.00 0 50 1 0
#> 98 24.00 0 34 1 0
#> 72 24.00 0 40 0 1
#> 112 24.00 0 61 0 0
#> 21 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 121.1 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 22 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 22.1 24.00 0 52 1 0
#> 27.1 24.00 0 63 1 0
#> 186.2 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 94.1 24.00 0 51 0 1
#> 67 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 62.1 24.00 0 71 0 0
#> 87 24.00 0 27 0 0
#> 176.1 24.00 0 43 0 1
#> 80.1 24.00 0 41 0 0
#> 21.1 24.00 0 47 0 0
#> 102 24.00 0 49 0 0
#> 142 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 109.2 24.00 0 48 0 0
#> 132.2 24.00 0 55 0 0
#> 182 24.00 0 35 0 0
#> 2 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#> 21.2 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 160.1 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 21.3 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 62.2 24.00 0 71 0 0
#> 120.1 24.00 0 68 0 1
#> 75 24.00 0 21 1 0
#> 160.2 24.00 0 31 1 0
#> 186.3 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 135.1 24.00 0 58 1 0
#> 115 24.00 0 NA 1 0
#> 186.4 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 135.2 24.00 0 58 1 0
#> 178 24.00 0 52 1 0
#> 198.1 24.00 0 66 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0594 NA NA NA
#> 2 age, Cure model -0.00334 NA NA NA
#> 3 grade_ii, Cure model -0.112 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0134 NA NA NA
#> 2 grade_ii, Survival model 0.845 NA NA NA
#> 3 grade_iii, Survival model 0.475 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.059438 -0.003339 -0.111654 1.094842
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 251 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.059437697 -0.003339332 -0.111654447 1.094841878
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01342448 0.84470089 0.47535330
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4633913809 0.2583432298 0.5166794503 0.0059098714 0.7934368170
#> [6] 0.0802228676 0.2583432298 0.4743250027 0.5166794503 0.9257038154
#> [11] 0.0528303204 0.5927870871 0.5596445442 0.7033257224 0.1616790382
#> [16] 0.6588725027 0.3987583631 0.7598685047 0.2867597140 0.1616790382
#> [21] 0.3780466460 0.4202689279 0.3066321754 0.8598923302 0.1616790382
#> [26] 0.8270855548 0.0528303204 0.5706478812 0.0340056017 0.9678773818
#> [31] 0.2394792549 0.4418428222 0.5927870871 0.4743250027 0.6588725027
#> [36] 0.8270855548 0.1109438169 0.1953286253 0.5927870871 0.0658004347
#> [41] 0.6588725027 0.0340056017 0.8598923302 0.8926698660 0.7598685047
#> [46] 0.9678773818 0.3472347826 0.1445577646 0.8926698660 0.5379247318
#> [51] 0.1953286253 0.6367032611 0.2213518388 0.3269036214 0.7259162691
#> [56] 0.3269036214 0.1616790382 0.9257038154 0.1109438169 0.6367032611
#> [61] 0.6255075463 0.0222186547 0.7372494169 0.1445577646 0.3066321754
#> [66] 0.8047039978 0.0004612388 0.1277480366 0.5379247318 0.5058883177
#> [71] 0.3577005358 0.0165862364 0.4310461096 0.9678773818 0.2213518388
#> [76] 0.9257038154 0.0802228676 0.3780466460 0.0459602039 0.8047039978
#> [81] 0.2583432298 0.4418428222 0.9146917290 0.2124486545 0.4743250027
#> [86] 0.8270855548 0.2488939092 0.0802228676 0.7486255276 0.9257038154
#> [91] 0.5706478812 0.0106774806 0.7033257224 0.2966378219 0.0658004347
#> [96] 0.0802228676 0.4094346686 0.7821340394 0.0284344856 0.0027381953
#> [101] 0.6920459091 0.3577005358 0.8816936834 0.1277480366 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 181 55 79 168 49 175 55.1 192 79.1 70 194 167 26
#> 16.46 19.34 16.23 23.72 12.19 21.91 19.34 16.44 16.23 7.38 22.40 15.55 15.77
#> 155 90 57 30 37 76 90.1 110 106 88 187 90.2 101
#> 13.08 20.94 14.46 17.43 12.52 19.22 20.94 17.56 16.67 18.37 9.92 20.94 9.97
#> 194.1 6 15 127 166 130 167.1 85 57.1 101.1 197 190 167.2
#> 22.40 15.64 22.68 3.53 19.98 16.47 15.55 16.44 14.46 9.97 21.60 20.81 15.55
#> 66 57.2 15.1 187.1 16 37.1 127.1 51 36 16.1 100 190.1 96
#> 22.13 14.46 22.68 9.92 8.71 12.52 3.53 18.23 21.19 8.71 16.07 20.81 14.54
#> 150 108 123 108.1 90.3 70.1 197.1 96.1 157 113 14 36.1 88.1
#> 20.33 18.29 13.00 18.29 20.94 7.38 21.60 14.54 15.10 22.86 12.89 21.19 18.37
#> 61 78 139 100.1 5 134 69 171 127.2 150.1 70.2 175.1 110.1
#> 10.12 23.88 21.49 16.07 16.43 17.81 23.23 16.57 3.53 20.33 7.38 21.91 17.56
#> 169 61.1 55.2 130.1 149 68 192.1 101.2 170 175.2 154 70.3 6.1
#> 22.41 10.12 19.34 16.47 8.37 20.62 16.44 9.97 19.54 21.91 12.63 7.38 15.64
#> 164 155.1 8 66.1 175.3 23 56 63 86 13 134.1 183 139.1
#> 23.60 13.08 18.43 22.13 21.91 16.92 12.21 22.77 23.81 14.34 17.81 9.24 21.49
#> 11 174 109 65 144 198 138 186 141 186.1 65.1 80 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 143 122 84 121 33 118 147 48 34 118.1 27 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 148 193 148.1 141.1 148.2 120 109.1 19 156 98 72 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 131 121.1 1 22 17 95 62 22.1 27.1 186.2 132 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 137 62.1 87 176.1 80.1 21.1 102 142 160 132.1 109.2 132.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 2 82 21.2 135 160.1 2.1 21.3 119 62.2 120.1 75 160.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.3 71 87.1 135.1 186.4 196 135.2 178 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[58]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01571924 1.35381441 0.78253926
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86967314 0.01355625 0.08233981
#> grade_iii, Cure model
#> 0.96454141
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 183 9.24 1 67 1 0
#> 101 9.97 1 10 0 1
#> 43 12.10 1 61 0 1
#> 184 17.77 1 38 0 0
#> 14 12.89 1 21 0 0
#> 183.1 9.24 1 67 1 0
#> 10 10.53 1 34 0 0
#> 18 15.21 1 49 1 0
#> 111 17.45 1 47 0 1
#> 130 16.47 1 53 0 1
#> 50 10.02 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 90 20.94 1 50 0 1
#> 45 17.42 1 54 0 1
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 5 16.43 1 51 0 1
#> 61.1 10.12 1 36 0 1
#> 24 23.89 1 38 0 0
#> 124 9.73 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 111.1 17.45 1 47 0 1
#> 5.1 16.43 1 51 0 1
#> 97 19.14 1 65 0 1
#> 170 19.54 1 43 0 1
#> 77 7.27 1 67 0 1
#> 40 18.00 1 28 1 0
#> 55 19.34 1 69 0 1
#> 50.1 10.02 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 166 19.98 1 48 0 0
#> 61.2 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 197 21.60 1 69 1 0
#> 107 11.18 1 54 1 0
#> 57 14.46 1 45 0 1
#> 45.1 17.42 1 54 0 1
#> 97.1 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 154 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 39 15.59 1 37 0 1
#> 99 21.19 1 38 0 1
#> 78.1 23.88 1 43 0 0
#> 194 22.40 1 38 0 1
#> 164.1 23.60 1 76 0 1
#> 177 12.53 1 75 0 0
#> 51 18.23 1 83 0 1
#> 125 15.65 1 67 1 0
#> 5.2 16.43 1 51 0 1
#> 8 18.43 1 32 0 0
#> 199 19.81 1 NA 0 1
#> 110.1 17.56 1 65 0 1
#> 86 23.81 1 58 0 1
#> 25.1 6.32 1 34 1 0
#> 155 13.08 1 26 0 0
#> 90.1 20.94 1 50 0 1
#> 18.1 15.21 1 49 1 0
#> 157 15.10 1 47 0 0
#> 154.1 12.63 1 20 1 0
#> 57.1 14.46 1 45 0 1
#> 90.2 20.94 1 50 0 1
#> 61.3 10.12 1 36 0 1
#> 117 17.46 1 26 0 1
#> 89 11.44 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 60 13.15 1 38 1 0
#> 188 16.16 1 46 0 1
#> 99.1 21.19 1 38 0 1
#> 15.1 22.68 1 48 0 0
#> 123 13.00 1 44 1 0
#> 76 19.22 1 54 0 1
#> 66 22.13 1 53 0 0
#> 134 17.81 1 47 1 0
#> 170.1 19.54 1 43 0 1
#> 175 21.91 1 43 0 0
#> 183.2 9.24 1 67 1 0
#> 164.2 23.60 1 76 0 1
#> 32 20.90 1 37 1 0
#> 159 10.55 1 50 0 1
#> 149 8.37 1 33 1 0
#> 155.1 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 99.2 21.19 1 38 0 1
#> 42 12.43 1 49 0 1
#> 57.2 14.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 79 16.23 1 54 1 0
#> 158.1 20.14 1 74 1 0
#> 99.3 21.19 1 38 0 1
#> 133 14.65 1 57 0 0
#> 130.1 16.47 1 53 0 1
#> 45.2 17.42 1 54 0 1
#> 91 5.33 1 61 0 1
#> 153 21.33 1 55 1 0
#> 179 18.63 1 42 0 0
#> 42.1 12.43 1 49 0 1
#> 100 16.07 1 60 0 0
#> 4.1 17.64 1 NA 0 1
#> 184.1 17.77 1 38 0 0
#> 30 17.43 1 78 0 0
#> 76.1 19.22 1 54 0 1
#> 57.3 14.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 78.2 23.88 1 43 0 0
#> 113 22.86 1 34 0 0
#> 183.3 9.24 1 67 1 0
#> 97.2 19.14 1 65 0 1
#> 147 24.00 0 76 1 0
#> 152 24.00 0 36 0 1
#> 118 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 173 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 22 24.00 0 52 1 0
#> 182 24.00 0 35 0 0
#> 31 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 48 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 62 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 118.1 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 34 24.00 0 36 0 0
#> 176 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 71 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 147.1 24.00 0 76 1 0
#> 191 24.00 0 60 0 1
#> 174 24.00 0 49 1 0
#> 193.1 24.00 0 45 0 1
#> 131 24.00 0 66 0 0
#> 182.1 24.00 0 35 0 0
#> 72 24.00 0 40 0 1
#> 147.2 24.00 0 76 1 0
#> 103.2 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 191.1 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 72.1 24.00 0 40 0 1
#> 193.2 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 80 24.00 0 41 0 0
#> 131.1 24.00 0 66 0 0
#> 176.1 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 104.1 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 196.1 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 126.1 24.00 0 48 0 0
#> 48.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 196.2 24.00 0 19 0 0
#> 193.3 24.00 0 45 0 1
#> 44 24.00 0 56 0 0
#> 121.1 24.00 0 57 1 0
#> 126.2 24.00 0 48 0 0
#> 141.1 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 9.1 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 73 24.00 0 NA 0 1
#> 35 24.00 0 51 0 0
#> 72.2 24.00 0 40 0 1
#> 71.1 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 73.1 24.00 0 NA 0 1
#> 173.1 24.00 0 19 0 1
#> 174.1 24.00 0 49 1 0
#> 20 24.00 0 46 1 0
#> 120 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 138.1 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 73.2 24.00 0 NA 0 1
#> 38 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 74.1 24.00 0 43 0 1
#> 94.1 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.870 NA NA NA
#> 2 age, Cure model 0.0136 NA NA NA
#> 3 grade_ii, Cure model 0.0823 NA NA NA
#> 4 grade_iii, Cure model 0.965 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0157 NA NA NA
#> 2 grade_ii, Survival model 1.35 NA NA NA
#> 3 grade_iii, Survival model 0.783 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86967 0.01356 0.08234 0.96454
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 247.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86967314 0.01355625 0.08233981 0.96454141
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01571924 1.35381441 0.78253926
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9100543982 0.9007671885 0.8260156373 0.4029542051 0.7591821034
#> [6] 0.9100543982 0.8543864536 0.6401178462 0.4543390026 0.5160317172
#> [11] 0.9461300915 0.1793591147 0.4851862027 0.2193830858 0.8638634594
#> [16] 0.5368473370 0.8638634594 0.0007336476 0.0045155903 0.2295737405
#> [21] 0.4543390026 0.5368473370 0.3095042622 0.2593508000 0.9643684925
#> [26] 0.3825080253 0.2791852615 0.0268639197 0.2491472060 0.8638634594
#> [31] 0.9734511345 0.1164800812 0.8355194486 0.6800635501 0.4851862027
#> [36] 0.3095042622 0.0590711310 0.7789477878 0.4233759241 0.6195838182
#> [41] 0.1404745791 0.0045155903 0.0804745380 0.0268639197 0.7976620432
#> [46] 0.3717373194 0.5990447947 0.5368473370 0.3503885974 0.4233759241
#> [51] 0.0191517067 0.9734511345 0.7294269989 0.1793591147 0.6401178462
#> [56] 0.6598913949 0.7789477878 0.6800635501 0.1793591147 0.8638634594
#> [61] 0.4440095423 0.5990447947 0.7195122473 0.5781851878 0.1404745791
#> [66] 0.0590711310 0.7493017879 0.2893813833 0.0916785330 0.3928441106
#> [71] 0.2593508000 0.1037149330 0.9100543982 0.0268639197 0.2094234442
#> [76] 0.8449527706 0.9553060893 0.7294269989 0.1404745791 0.8071522472
#> [81] 0.6800635501 0.6299015057 0.7690987052 0.5678004033 0.2295737405
#> [86] 0.1404745791 0.6699325406 0.5160317172 0.4851862027 0.9911153351
#> [91] 0.1288289153 0.3398128299 0.8071522472 0.5885585644 0.4029542051
#> [96] 0.4747222792 0.2893813833 0.6800635501 0.3610920853 0.0045155903
#> [101] 0.0492958913 0.9100543982 0.3095042622 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 183 101 43 184 14 183.1 10 18 111 130 16 90 45
#> 9.24 9.97 12.10 17.77 12.89 9.24 10.53 15.21 17.45 16.47 8.71 20.94 17.42
#> 68 61 5 61.1 24 78 158 111.1 5.1 97 170 77 40
#> 20.62 10.12 16.43 10.12 23.89 23.88 20.14 17.45 16.43 19.14 19.54 7.27 18.00
#> 55 164 166 61.2 25 197 107 57 45.1 97.1 15 154 110
#> 19.34 23.60 19.98 10.12 6.32 21.60 11.18 14.46 17.42 19.14 22.68 12.63 17.56
#> 39 99 78.1 194 164.1 177 51 125 5.2 8 110.1 86 25.1
#> 15.59 21.19 23.88 22.40 23.60 12.53 18.23 15.65 16.43 18.43 17.56 23.81 6.32
#> 155 90.1 18.1 157 154.1 57.1 90.2 61.3 117 125.1 60 188 99.1
#> 13.08 20.94 15.21 15.10 12.63 14.46 20.94 10.12 17.46 15.65 13.15 16.16 21.19
#> 15.1 123 76 66 134 170.1 175 183.2 164.2 32 159 149 155.1
#> 22.68 13.00 19.22 22.13 17.81 19.54 21.91 9.24 23.60 20.90 10.55 8.37 13.08
#> 99.2 42 57.2 167 140 79 158.1 99.3 133 130.1 45.2 91 153
#> 21.19 12.43 14.46 15.55 12.68 16.23 20.14 21.19 14.65 16.47 17.42 5.33 21.33
#> 179 42.1 100 184.1 30 76.1 57.3 108 78.2 113 183.3 97.2 147
#> 18.63 12.43 16.07 17.77 17.43 19.22 14.46 18.29 23.88 22.86 9.24 19.14 24.00
#> 152 118 74 193 173 3 83 64 22 182 31 103 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 62 82 118.1 138 102 34 176 84 71 104 147.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 193.1 131 182.1 72 147.2 103.2 9 126 156 132 191.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 148 72.1 193.2 196 80 131.1 176.1 162 104.1 33 121 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 95 112 126.1 48.1 141 196.2 193.3 44 121.1 126.2 141.1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 44.1 35 72.2 71.1 102.1 173.1 174.1 20 120 172 198 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 47 38 62.1 74.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[59]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005564601 0.456483859 0.285692169
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.75885508 0.01165881 0.45460468
#> grade_iii, Cure model
#> 0.75605855
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 123 13.00 1 44 1 0
#> 58 19.34 1 39 0 0
#> 70 7.38 1 30 1 0
#> 4 17.64 1 NA 0 1
#> 51 18.23 1 83 0 1
#> 127 3.53 1 62 0 1
#> 130 16.47 1 53 0 1
#> 60 13.15 1 38 1 0
#> 187 9.92 1 39 1 0
#> 42 12.43 1 49 0 1
#> 150 20.33 1 48 0 0
#> 158 20.14 1 74 1 0
#> 76 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 69 23.23 1 25 0 1
#> 79 16.23 1 54 1 0
#> 30 17.43 1 78 0 0
#> 58.1 19.34 1 39 0 0
#> 117 17.46 1 26 0 1
#> 99 21.19 1 38 0 1
#> 111 17.45 1 47 0 1
#> 10 10.53 1 34 0 0
#> 26 15.77 1 49 0 1
#> 125 15.65 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 56 12.21 1 60 0 0
#> 97 19.14 1 65 0 1
#> 79.1 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 113 22.86 1 34 0 0
#> 183 9.24 1 67 1 0
#> 124 9.73 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 43 12.10 1 61 0 1
#> 199 19.81 1 NA 0 1
#> 169 22.41 1 46 0 0
#> 107 11.18 1 54 1 0
#> 130.1 16.47 1 53 0 1
#> 69.1 23.23 1 25 0 1
#> 105 19.75 1 60 0 0
#> 150.1 20.33 1 48 0 0
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 6 15.64 1 39 0 0
#> 66 22.13 1 53 0 0
#> 111.1 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 41 18.02 1 40 1 0
#> 166 19.98 1 48 0 0
#> 4.1 17.64 1 NA 0 1
#> 10.1 10.53 1 34 0 0
#> 57 14.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 89 11.44 1 NA 0 0
#> 8.1 18.43 1 32 0 0
#> 30.2 17.43 1 78 0 0
#> 68 20.62 1 44 0 0
#> 153 21.33 1 55 1 0
#> 8.2 18.43 1 32 0 0
#> 190 20.81 1 42 1 0
#> 159.1 10.55 1 50 0 1
#> 145 10.07 1 65 1 0
#> 180 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 58.2 19.34 1 39 0 0
#> 190.1 20.81 1 42 1 0
#> 39.1 15.59 1 37 0 1
#> 43.1 12.10 1 61 0 1
#> 45.1 17.42 1 54 0 1
#> 90 20.94 1 50 0 1
#> 79.2 16.23 1 54 1 0
#> 69.2 23.23 1 25 0 1
#> 60.1 13.15 1 38 1 0
#> 159.2 10.55 1 50 0 1
#> 134 17.81 1 47 1 0
#> 159.3 10.55 1 50 0 1
#> 159.4 10.55 1 50 0 1
#> 140 12.68 1 59 1 0
#> 108 18.29 1 39 0 1
#> 117.1 17.46 1 26 0 1
#> 92 22.92 1 47 0 1
#> 129 23.41 1 53 1 0
#> 60.2 13.15 1 38 1 0
#> 52 10.42 1 52 0 1
#> 26.1 15.77 1 49 0 1
#> 14 12.89 1 21 0 0
#> 29 15.45 1 68 1 0
#> 170 19.54 1 43 0 1
#> 155 13.08 1 26 0 0
#> 114 13.68 1 NA 0 0
#> 57.1 14.46 1 45 0 1
#> 195 11.76 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 159.5 10.55 1 50 0 1
#> 158.1 20.14 1 74 1 0
#> 23 16.92 1 61 0 0
#> 78 23.88 1 43 0 0
#> 58.3 19.34 1 39 0 0
#> 91 5.33 1 61 0 1
#> 42.1 12.43 1 49 0 1
#> 114.1 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 70.2 7.38 1 30 1 0
#> 149 8.37 1 33 1 0
#> 145.1 10.07 1 65 1 0
#> 8.3 18.43 1 32 0 0
#> 41.1 18.02 1 40 1 0
#> 17 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 121 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 102 24.00 0 49 0 0
#> 87 24.00 0 27 0 0
#> 148 24.00 0 61 1 0
#> 185 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 46.1 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 121.1 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 83 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 74 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 80 24.00 0 41 0 0
#> 148.1 24.00 0 61 1 0
#> 46.2 24.00 0 71 0 0
#> 7.1 24.00 0 37 1 0
#> 62 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 198 24.00 0 66 0 1
#> 182 24.00 0 35 0 0
#> 82 24.00 0 34 0 0
#> 87.1 24.00 0 27 0 0
#> 47 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 95 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 47.1 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 161 24.00 0 45 0 0
#> 146 24.00 0 63 1 0
#> 84.1 24.00 0 39 0 1
#> 17.1 24.00 0 38 0 1
#> 7.2 24.00 0 37 1 0
#> 87.2 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 162 24.00 0 51 0 0
#> 196.1 24.00 0 19 0 0
#> 191 24.00 0 60 0 1
#> 198.1 24.00 0 66 0 1
#> 28 24.00 0 67 1 0
#> 83.1 24.00 0 6 0 0
#> 53 24.00 0 32 0 1
#> 54.1 24.00 0 53 1 0
#> 47.2 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 103.1 24.00 0 56 1 0
#> 182.1 24.00 0 35 0 0
#> 2.1 24.00 0 9 0 0
#> 174 24.00 0 49 1 0
#> 151 24.00 0 42 0 0
#> 162.1 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 186 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 67.1 24.00 0 25 0 0
#> 193.1 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 28.1 24.00 0 67 1 0
#> 35 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 83.2 24.00 0 6 0 0
#> 118 24.00 0 44 1 0
#> 148.2 24.00 0 61 1 0
#> 82.1 24.00 0 34 0 0
#> 80.1 24.00 0 41 0 0
#> 2.2 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 54.2 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#> 161.1 24.00 0 45 0 0
#> 120.1 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 120.2 24.00 0 68 0 1
#> 65 24.00 0 57 1 0
#> 119.1 24.00 0 17 0 0
#> 172 24.00 0 41 0 0
#> 109.1 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.759 NA NA NA
#> 2 age, Cure model 0.0117 NA NA NA
#> 3 grade_ii, Cure model 0.455 NA NA NA
#> 4 grade_iii, Cure model 0.756 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00556 NA NA NA
#> 2 grade_ii, Survival model 0.456 NA NA NA
#> 3 grade_iii, Survival model 0.286 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.75886 0.01166 0.45460 0.75606
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.75885508 0.01165881 0.45460468 0.75605855
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005564601 0.456483859 0.285692169
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.88751573 0.82941886 0.43367788 0.97137654 0.53883315 0.99429573
#> [7] 0.65746726 0.80289680 0.95370678 0.84917687 0.35831113 0.38115658
#> [13] 0.47264737 0.63325469 0.13776725 0.68107239 0.60871171 0.43367788
#> [19] 0.57466411 0.29668483 0.59186620 0.92359178 0.71101270 0.72574466
#> [25] 0.72574466 0.76846941 0.86206471 0.48253854 0.68107239 0.74729616
#> [31] 0.20393882 0.95963869 0.08247720 0.86851371 0.23683568 0.88120082
#> [37] 0.65746726 0.13776725 0.41285896 0.35831113 0.22057463 0.77542405
#> [43] 0.74010022 0.25277797 0.59186620 0.26838309 0.60871171 0.54808514
#> [49] 0.40225430 0.92359178 0.78928211 0.49224849 0.49224849 0.60871171
#> [55] 0.34646552 0.28293820 0.49224849 0.32296032 0.88751573 0.94180895
#> [61] 0.78236010 0.67322020 0.43367788 0.32296032 0.74729616 0.86851371
#> [67] 0.63325469 0.31003332 0.68107239 0.13776725 0.80289680 0.88751573
#> [73] 0.56585483 0.88751573 0.88751573 0.84263377 0.52940109 0.57466411
#> [79] 0.18701645 0.11378189 0.80289680 0.93574380 0.71101270 0.83602955
#> [85] 0.76144656 0.42335676 0.82275417 0.78928211 0.97137654 0.88751573
#> [91] 0.38115658 0.64938978 0.03753695 0.43367788 0.98856256 0.84917687
#> [97] 0.70349101 0.97137654 0.96552361 0.94180895 0.49224849 0.54808514
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 159 123 58 70 51 127 130 60 187 42 150 158 76
#> 10.55 13.00 19.34 7.38 18.23 3.53 16.47 13.15 9.92 12.43 20.33 20.14 19.22
#> 45 69 79 30 58.1 117 99 111 10 26 125 125.1 18
#> 17.42 23.23 16.23 17.43 19.34 17.46 21.19 17.45 10.53 15.77 15.65 15.65 15.21
#> 56 97 79.1 39 113 183 86 43 169 107 130.1 69.1 105
#> 12.21 19.14 16.23 15.59 22.86 9.24 23.81 12.10 22.41 11.18 16.47 23.23 19.75
#> 150.1 15 157 6 66 111.1 139 30.1 41 166 10.1 57 8
#> 20.33 22.68 15.10 15.64 22.13 17.45 21.49 17.43 18.02 19.98 10.53 14.46 18.43
#> 8.1 30.2 68 153 8.2 190 159.1 145 180 5 58.2 190.1 39.1
#> 18.43 17.43 20.62 21.33 18.43 20.81 10.55 10.07 14.82 16.43 19.34 20.81 15.59
#> 43.1 45.1 90 79.2 69.2 60.1 159.2 134 159.3 159.4 140 108 117.1
#> 12.10 17.42 20.94 16.23 23.23 13.15 10.55 17.81 10.55 10.55 12.68 18.29 17.46
#> 92 129 60.2 52 26.1 14 29 170 155 57.1 70.1 159.5 158.1
#> 22.92 23.41 13.15 10.42 15.77 12.89 15.45 19.54 13.08 14.46 7.38 10.55 20.14
#> 23 78 58.3 91 42.1 100 70.2 149 145.1 8.3 41.1 17 7
#> 16.92 23.88 19.34 5.33 12.43 16.07 7.38 8.37 10.07 18.43 18.02 24.00 24.00
#> 2 142 193 121 103 102 87 148 185 46 109 67 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 121.1 119 83 135 74 126 80 148.1 46.2 7.1 62 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 182 82 87.1 47 200 95 84 47.1 196 161 146 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 7.2 87.2 54 162 196.1 191 198.1 28 83.1 53 54.1 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 103.1 182.1 2.1 174 151 162.1 173 186 67.1 193.1 176 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 176.1 120 83.2 118 148.2 82.1 80.1 2.2 165 54.2 132 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 22 120.2 65 119.1 172 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[60]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009334188 0.638884577 -0.195162048
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.4357570 -0.0158276 0.4544604
#> grade_iii, Cure model
#> 1.1074292
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 93 10.33 1 52 0 1
#> 51 18.23 1 83 0 1
#> 29 15.45 1 68 1 0
#> 124 9.73 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 153 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 16 8.71 1 71 0 1
#> 4 17.64 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 25 6.32 1 34 1 0
#> 6 15.64 1 39 0 0
#> 68 20.62 1 44 0 0
#> 113 22.86 1 34 0 0
#> 42 12.43 1 49 0 1
#> 49 12.19 1 48 1 0
#> 199 19.81 1 NA 0 1
#> 55 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 6.1 15.64 1 39 0 0
#> 78 23.88 1 43 0 0
#> 153.1 21.33 1 55 1 0
#> 70 7.38 1 30 1 0
#> 179 18.63 1 42 0 0
#> 92 22.92 1 47 0 1
#> 86 23.81 1 58 0 1
#> 26 15.77 1 49 0 1
#> 128 20.35 1 35 0 1
#> 10 10.53 1 34 0 0
#> 32 20.90 1 37 1 0
#> 180 14.82 1 37 0 0
#> 108 18.29 1 39 0 1
#> 69 23.23 1 25 0 1
#> 69.1 23.23 1 25 0 1
#> 6.2 15.64 1 39 0 0
#> 86.1 23.81 1 58 0 1
#> 180.1 14.82 1 37 0 0
#> 114 13.68 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 108.1 18.29 1 39 0 1
#> 171 16.57 1 41 0 1
#> 136 21.83 1 43 0 1
#> 101 9.97 1 10 0 1
#> 128.1 20.35 1 35 0 1
#> 24 23.89 1 38 0 0
#> 91 5.33 1 61 0 1
#> 145 10.07 1 65 1 0
#> 60 13.15 1 38 1 0
#> 23 16.92 1 61 0 0
#> 179.1 18.63 1 42 0 0
#> 145.1 10.07 1 65 1 0
#> 32.1 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 88 18.37 1 47 0 0
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 110 17.56 1 65 0 1
#> 139 21.49 1 63 1 0
#> 123.1 13.00 1 44 1 0
#> 179.2 18.63 1 42 0 0
#> 164 23.60 1 76 0 1
#> 29.1 15.45 1 68 1 0
#> 39 15.59 1 37 0 1
#> 133 14.65 1 57 0 0
#> 58 19.34 1 39 0 0
#> 60.1 13.15 1 38 1 0
#> 105 19.75 1 60 0 0
#> 89 11.44 1 NA 0 0
#> 192 16.44 1 31 1 0
#> 59 10.16 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 157 15.10 1 47 0 0
#> 60.2 13.15 1 38 1 0
#> 41 18.02 1 40 1 0
#> 69.2 23.23 1 25 0 1
#> 43 12.10 1 61 0 1
#> 171.1 16.57 1 41 0 1
#> 63 22.77 1 31 1 0
#> 113.1 22.86 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 58.1 19.34 1 39 0 0
#> 154.1 12.63 1 20 1 0
#> 125 15.65 1 67 1 0
#> 166 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 134 17.81 1 47 1 0
#> 69.3 23.23 1 25 0 1
#> 50 10.02 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 77.1 7.27 1 67 0 1
#> 100 16.07 1 60 0 0
#> 92.1 22.92 1 47 0 1
#> 192.1 16.44 1 31 1 0
#> 41.1 18.02 1 40 1 0
#> 66 22.13 1 53 0 0
#> 199.1 19.81 1 NA 0 1
#> 49.1 12.19 1 48 1 0
#> 41.2 18.02 1 40 1 0
#> 136.1 21.83 1 43 0 1
#> 199.2 19.81 1 NA 0 1
#> 41.3 18.02 1 40 1 0
#> 70.1 7.38 1 30 1 0
#> 179.3 18.63 1 42 0 0
#> 18 15.21 1 49 1 0
#> 195 11.76 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 58.2 19.34 1 39 0 0
#> 92.2 22.92 1 47 0 1
#> 40.1 18.00 1 28 1 0
#> 136.2 21.83 1 43 0 1
#> 94 24.00 0 51 0 1
#> 21 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 132 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 132.1 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 31.1 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 196 24.00 0 19 0 0
#> 2 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#> 135 24.00 0 58 1 0
#> 12 24.00 0 63 0 0
#> 119 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 1 24.00 0 23 1 0
#> 196.1 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 28 24.00 0 67 1 0
#> 27 24.00 0 63 1 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 46.1 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 27.1 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 126.1 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 82.1 24.00 0 34 0 0
#> 138 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 120 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 31.2 24.00 0 36 0 1
#> 62.1 24.00 0 71 0 0
#> 27.2 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 28.1 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 95.1 24.00 0 68 0 1
#> 115.1 24.00 0 NA 1 0
#> 176 24.00 0 43 0 1
#> 20.1 24.00 0 46 1 0
#> 142 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 163 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 185.2 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 162.2 24.00 0 51 0 0
#> 82.2 24.00 0 34 0 0
#> 65 24.00 0 57 1 0
#> 98.1 24.00 0 34 1 0
#> 147 24.00 0 76 1 0
#> 62.2 24.00 0 71 0 0
#> 156.2 24.00 0 50 1 0
#> 12.1 24.00 0 63 0 0
#> 64.1 24.00 0 43 0 0
#> 160 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 131.1 24.00 0 66 0 0
#> 196.2 24.00 0 19 0 0
#> 47 24.00 0 38 0 1
#> 82.3 24.00 0 34 0 0
#> 31.3 24.00 0 36 0 1
#> 121 24.00 0 57 1 0
#> 119.1 24.00 0 17 0 0
#> 109 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 35 24.00 0 51 0 0
#> 28.2 24.00 0 67 1 0
#> 174.1 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.436 NA NA NA
#> 2 age, Cure model -0.0158 NA NA NA
#> 3 grade_ii, Cure model 0.454 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00933 NA NA NA
#> 2 grade_ii, Survival model 0.639 NA NA NA
#> 3 grade_iii, Survival model -0.195 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.43576 -0.01583 0.45446 1.10743
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 246.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.4357570 -0.0158276 0.4544604 1.1074292
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009334188 0.638884577 -0.195162048
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.93621079 0.62446512 0.79042939 0.86095143 0.40811051 0.55175034
#> [7] 0.96336783 0.68887326 0.98964022 0.76276149 0.46355485 0.28681333
#> [13] 0.89066037 0.90237634 0.51429001 0.89653272 0.76276149 0.07319979
#> [19] 0.40811051 0.96871576 0.56127923 0.23605318 0.10310034 0.74848554
#> [25] 0.47387603 0.93062569 0.43159392 0.81674482 0.60642870 0.16708269
#> [31] 0.16708269 0.76276149 0.10310034 0.81674482 0.66550020 0.60642870
#> [37] 0.71173408 0.35149266 0.95258409 0.47387603 0.03629965 0.99482623
#> [43] 0.94178470 0.84251325 0.70416996 0.56127923 0.94178470 0.43159392
#> [49] 0.87296819 0.59729207 0.95800215 0.83608060 0.69654299 0.39447052
#> [55] 0.86095143 0.56127923 0.14601470 0.79042939 0.78347362 0.82964203
#> [61] 0.51429001 0.84251325 0.50430572 0.72671660 0.92502803 0.81022794
#> [67] 0.84251325 0.63344680 0.16708269 0.91373752 0.71173408 0.32022629
#> [73] 0.28681333 0.91941979 0.51429001 0.87296819 0.75570914 0.49417081
#> [79] 0.97920804 0.68116700 0.16708269 0.88477638 0.97920804 0.74124097
#> [85] 0.23605318 0.72671660 0.63344680 0.33609202 0.90237634 0.63344680
#> [91] 0.35149266 0.63344680 0.96871576 0.56127923 0.80368206 0.45311564
#> [97] 0.51429001 0.23605318 0.66550020 0.35149266 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 93 51 29 123 153 97 16 184 25 6 68 113 42
#> 10.33 18.23 15.45 13.00 21.33 19.14 8.71 17.77 6.32 15.64 20.62 22.86 12.43
#> 49 55 56 6.1 78 153.1 70 179 92 86 26 128 10
#> 12.19 19.34 12.21 15.64 23.88 21.33 7.38 18.63 22.92 23.81 15.77 20.35 10.53
#> 32 180 108 69 69.1 6.2 86.1 180.1 40 108.1 171 136 101
#> 20.90 14.82 18.29 23.23 23.23 15.64 23.81 14.82 18.00 18.29 16.57 21.83 9.97
#> 128.1 24 91 145 60 23 179.1 145.1 32.1 154 88 187 96
#> 20.35 23.89 5.33 10.07 13.15 16.92 18.63 10.07 20.90 12.63 18.37 9.92 14.54
#> 110 139 123.1 179.2 164 29.1 39 133 58 60.1 105 192 159
#> 17.56 21.49 13.00 18.63 23.60 15.45 15.59 14.65 19.34 13.15 19.75 16.44 10.55
#> 157 60.2 41 69.2 43 171.1 63 113.1 107 58.1 154.1 125 166
#> 15.10 13.15 18.02 23.23 12.10 16.57 22.77 22.86 11.18 19.34 12.63 15.65 19.98
#> 77 134 69.3 177 77.1 100 92.1 192.1 41.1 66 49.1 41.2 136.1
#> 7.27 17.81 23.23 12.53 7.27 16.07 22.92 16.44 18.02 22.13 12.19 18.02 21.83
#> 41.3 70.1 179.3 18 190 58.2 92.2 40.1 136.2 94 21 46 31
#> 18.02 7.38 18.63 15.21 20.81 19.34 22.92 18.00 21.83 24.00 24.00 24.00 24.00
#> 193 132 126 144 132.1 141 172 19 31.1 196 2 82 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 119 156 80 33 1 196.1 103 28 27 74 185 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 143 46.1 191 27.1 54 131 185.1 95 126.1 98 82.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 120 62 31.2 62.1 27.2 162 28.1 173 95.1 176 20.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 138.1 64 163 174 185.2 162.1 162.2 82.2 65 98.1 147 62.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 12.1 64.1 160 178.1 131.1 196.2 47 82.3 31.3 121 119.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 35 28.2 174.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[61]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001312531 0.803646914 0.486291701
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.8117387 0.0144759 0.4383128
#> grade_iii, Cure model
#> 0.7657468
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 133 14.65 1 57 0 0
#> 66 22.13 1 53 0 0
#> 179 18.63 1 42 0 0
#> 90 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 184 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 60 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 32 20.90 1 37 1 0
#> 6 15.64 1 39 0 0
#> 30 17.43 1 78 0 0
#> 149 8.37 1 33 1 0
#> 56 12.21 1 60 0 0
#> 40 18.00 1 28 1 0
#> 113 22.86 1 34 0 0
#> 51 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 18.1 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 90.1 20.94 1 50 0 1
#> 70 7.38 1 30 1 0
#> 199 19.81 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 36 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 150 20.33 1 48 0 0
#> 155 13.08 1 26 0 0
#> 168 23.72 1 70 0 0
#> 92 22.92 1 47 0 1
#> 13 14.34 1 54 0 1
#> 184.1 17.77 1 38 0 0
#> 190 20.81 1 42 1 0
#> 187 9.92 1 39 1 0
#> 58 19.34 1 39 0 0
#> 181 16.46 1 45 0 1
#> 158 20.14 1 74 1 0
#> 130 16.47 1 53 0 1
#> 170 19.54 1 43 0 1
#> 134 17.81 1 47 1 0
#> 169 22.41 1 46 0 0
#> 149.1 8.37 1 33 1 0
#> 170.1 19.54 1 43 0 1
#> 18.2 15.21 1 49 1 0
#> 55 19.34 1 69 0 1
#> 51.1 18.23 1 83 0 1
#> 25 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 4 17.64 1 NA 0 1
#> 43.1 12.10 1 61 0 1
#> 66.2 22.13 1 53 0 0
#> 100 16.07 1 60 0 0
#> 88 18.37 1 47 0 0
#> 106 16.67 1 49 1 0
#> 150.1 20.33 1 48 0 0
#> 106.1 16.67 1 49 1 0
#> 199.1 19.81 1 NA 0 1
#> 5.1 16.43 1 51 0 1
#> 158.1 20.14 1 74 1 0
#> 100.1 16.07 1 60 0 0
#> 106.2 16.67 1 49 1 0
#> 166 19.98 1 48 0 0
#> 88.1 18.37 1 47 0 0
#> 49 12.19 1 48 1 0
#> 88.2 18.37 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 168.1 23.72 1 70 0 0
#> 25.1 6.32 1 34 1 0
#> 96 14.54 1 33 0 1
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 150.2 20.33 1 48 0 0
#> 25.2 6.32 1 34 1 0
#> 60.1 13.15 1 38 1 0
#> 188 16.16 1 46 0 1
#> 166.1 19.98 1 48 0 0
#> 85 16.44 1 36 0 0
#> 97 19.14 1 65 0 1
#> 39 15.59 1 37 0 1
#> 106.3 16.67 1 49 1 0
#> 184.2 17.77 1 38 0 0
#> 134.1 17.81 1 47 1 0
#> 32.1 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 187.1 9.92 1 39 1 0
#> 49.1 12.19 1 48 1 0
#> 153 21.33 1 55 1 0
#> 45 17.42 1 54 0 1
#> 10 10.53 1 34 0 0
#> 5.2 16.43 1 51 0 1
#> 91 5.33 1 61 0 1
#> 100.2 16.07 1 60 0 0
#> 49.2 12.19 1 48 1 0
#> 16 8.71 1 71 0 1
#> 113.1 22.86 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 105 19.75 1 60 0 0
#> 155.1 13.08 1 26 0 0
#> 108 18.29 1 39 0 1
#> 69 23.23 1 25 0 1
#> 96.1 14.54 1 33 0 1
#> 127 3.53 1 62 0 1
#> 124 9.73 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 96.2 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 85.1 16.44 1 36 0 0
#> 78 23.88 1 43 0 0
#> 189.1 10.51 1 NA 1 0
#> 49.3 12.19 1 48 1 0
#> 21 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 135 24.00 0 58 1 0
#> 146 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 71 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 182 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 141 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 11 24.00 0 42 0 1
#> 82 24.00 0 34 0 0
#> 132 24.00 0 55 0 0
#> 98.1 24.00 0 34 1 0
#> 138 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 22 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 161 24.00 0 45 0 0
#> 53.1 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 182.1 24.00 0 35 0 0
#> 27 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 34 24.00 0 36 0 0
#> 9 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 118 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 118.1 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 135.1 24.00 0 58 1 0
#> 121 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 132.1 24.00 0 55 0 0
#> 83.1 24.00 0 6 0 0
#> 44 24.00 0 56 0 0
#> 200.1 24.00 0 64 0 0
#> 109 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 162.1 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 119 24.00 0 17 0 0
#> 74 24.00 0 43 0 1
#> 83.2 24.00 0 6 0 0
#> 48.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 44.1 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 35 24.00 0 51 0 0
#> 135.2 24.00 0 58 1 0
#> 147 24.00 0 76 1 0
#> 44.2 24.00 0 56 0 0
#> 144.1 24.00 0 28 0 1
#> 46 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 46.1 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 142 24.00 0 53 0 0
#> 161.1 24.00 0 45 0 0
#> 20.1 24.00 0 46 1 0
#> 11.1 24.00 0 42 0 1
#> 102.1 24.00 0 49 0 0
#> 34.2 24.00 0 36 0 0
#> 109.1 24.00 0 48 0 0
#> 87.1 24.00 0 27 0 0
#> 64.1 24.00 0 43 0 0
#> 176.1 24.00 0 43 0 1
#> 160.1 24.00 0 31 1 0
#> 132.2 24.00 0 55 0 0
#> 64.2 24.00 0 43 0 0
#> 109.2 24.00 0 48 0 0
#> 44.3 24.00 0 56 0 0
#> 185 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.812 NA NA NA
#> 2 age, Cure model 0.0145 NA NA NA
#> 3 grade_ii, Cure model 0.438 NA NA NA
#> 4 grade_iii, Cure model 0.766 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00131 NA NA NA
#> 2 grade_ii, Survival model 0.804 NA NA NA
#> 3 grade_iii, Survival model 0.486 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.81174 0.01448 0.43831 0.76575
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 260.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.8117387 0.0144759 0.4383128 0.7657468
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001312531 0.803646914 0.486291701
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.84063761 0.77572063 0.16597654 0.45823563 0.24827352 0.91615948
#> [7] 0.56068468 0.89584030 0.81219560 0.92292465 0.27275654 0.73823341
#> [13] 0.58662771 0.94938774 0.84778620 0.53420339 0.10587372 0.50618610
#> [19] 0.75364071 0.75364071 0.69219022 0.24827352 0.96230638 0.88220626
#> [25] 0.23501404 0.16597654 0.31675309 0.82641250 0.03445252 0.08929599
#> [31] 0.80491170 0.56068468 0.29499130 0.92963810 0.41914344 0.64444869
#> [37] 0.34851346 0.63630544 0.39934166 0.54329274 0.15138996 0.94938774
#> [43] 0.39934166 0.75364071 0.41914344 0.50618610 0.96873782 0.66863305
#> [49] 0.88220626 0.16597654 0.71531046 0.46794035 0.60414374 0.31675309
#> [55] 0.60414374 0.66863305 0.34851346 0.71531046 0.60414374 0.36874117
#> [61] 0.46794035 0.85493937 0.46794035 0.69219022 0.03445252 0.96873782
#> [67] 0.78315670 0.13688627 0.20670940 0.31675309 0.96873782 0.81219560
#> [73] 0.70760529 0.36874117 0.65253746 0.44854193 0.74595890 0.60414374
#> [79] 0.56068468 0.54329274 0.27275654 0.43874378 0.92963810 0.85493937
#> [85] 0.22134859 0.59541890 0.90262742 0.66863305 0.98748299 0.71531046
#> [91] 0.85493937 0.94280391 0.10587372 0.90262742 0.38903712 0.82641250
#> [97] 0.49655974 0.07093180 0.78315670 0.99375133 0.30586131 0.78315670
#> [103] 0.52493215 0.65253746 0.01195943 0.85493937 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 177 133 66 179 90 93 184 107 60 145 32 6 30
#> 12.53 14.65 22.13 18.63 20.94 10.33 17.77 11.18 13.15 10.07 20.90 15.64 17.43
#> 149 56 40 113 51 18 18.1 79 90.1 70 43 36 66.1
#> 8.37 12.21 18.00 22.86 18.23 15.21 15.21 16.23 20.94 7.38 12.10 21.19 22.13
#> 150 155 168 92 13 184.1 190 187 58 181 158 130 170
#> 20.33 13.08 23.72 22.92 14.34 17.77 20.81 9.92 19.34 16.46 20.14 16.47 19.54
#> 134 169 149.1 170.1 18.2 55 51.1 25 5 43.1 66.2 100 88
#> 17.81 22.41 8.37 19.54 15.21 19.34 18.23 6.32 16.43 12.10 22.13 16.07 18.37
#> 106 150.1 106.1 5.1 158.1 100.1 106.2 166 88.1 49 88.2 79.1 168.1
#> 16.67 20.33 16.67 16.43 20.14 16.07 16.67 19.98 18.37 12.19 18.37 16.23 23.72
#> 25.1 96 63 175 150.2 25.2 60.1 188 166.1 85 97 39 106.3
#> 6.32 14.54 22.77 21.91 20.33 6.32 13.15 16.16 19.98 16.44 19.14 15.59 16.67
#> 184.2 134.1 32.1 76 187.1 49.1 153 45 10 5.2 91 100.2 49.2
#> 17.77 17.81 20.90 19.22 9.92 12.19 21.33 17.42 10.53 16.43 5.33 16.07 12.19
#> 16 113.1 10.1 105 155.1 108 69 96.1 127 68 96.2 41 85.1
#> 8.71 22.86 10.53 19.75 13.08 18.29 23.23 14.54 3.53 20.62 14.54 18.02 16.44
#> 78 49.3 21 48 200 72 165 162 126 102 94 135 146
#> 23.88 12.19 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 71 176 87 182 1 141 53 11 82 132 98.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 22 20 161 53.1 122 182.1 27 64 34 9 83 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 172 54 118.1 12 135.1 121 146.1 116 160 34.1 132.1 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 200.1 109 65 162.1 19 119 74 83.2 48.1 95 44.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 135.2 147 44.2 144.1 46 31 46.1 198 142 161.1 20.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 34.2 109.1 87.1 64.1 176.1 160.1 132.2 64.2 109.2 44.3 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[62]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01768066 0.51038616 0.06928135
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.67806873 0.03411394 -0.10674047
#> grade_iii, Cure model
#> 0.78857694
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 5 16.43 1 51 0 1
#> 105 19.75 1 60 0 0
#> 100 16.07 1 60 0 0
#> 60 13.15 1 38 1 0
#> 190 20.81 1 42 1 0
#> 128 20.35 1 35 0 1
#> 171 16.57 1 41 0 1
#> 183 9.24 1 67 1 0
#> 127 3.53 1 62 0 1
#> 89 11.44 1 NA 0 0
#> 49 12.19 1 48 1 0
#> 57 14.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 124.1 9.73 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 164 23.60 1 76 0 1
#> 58 19.34 1 39 0 0
#> 194 22.40 1 38 0 1
#> 30 17.43 1 78 0 0
#> 56 12.21 1 60 0 0
#> 164.1 23.60 1 76 0 1
#> 5.1 16.43 1 51 0 1
#> 4 17.64 1 NA 0 1
#> 52 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 86 23.81 1 58 0 1
#> 91 5.33 1 61 0 1
#> 108 18.29 1 39 0 1
#> 130 16.47 1 53 0 1
#> 192 16.44 1 31 1 0
#> 192.1 16.44 1 31 1 0
#> 52.1 10.42 1 52 0 1
#> 139 21.49 1 63 1 0
#> 157 15.10 1 47 0 0
#> 41 18.02 1 40 1 0
#> 77 7.27 1 67 0 1
#> 192.2 16.44 1 31 1 0
#> 56.1 12.21 1 60 0 0
#> 179 18.63 1 42 0 0
#> 125 15.65 1 67 1 0
#> 51.1 18.23 1 83 0 1
#> 168 23.72 1 70 0 0
#> 123 13.00 1 44 1 0
#> 79 16.23 1 54 1 0
#> 197 21.60 1 69 1 0
#> 61 10.12 1 36 0 1
#> 45 17.42 1 54 0 1
#> 107 11.18 1 54 1 0
#> 169 22.41 1 46 0 0
#> 25 6.32 1 34 1 0
#> 187 9.92 1 39 1 0
#> 68 20.62 1 44 0 0
#> 68.1 20.62 1 44 0 0
#> 96 14.54 1 33 0 1
#> 4.1 17.64 1 NA 0 1
#> 117 17.46 1 26 0 1
#> 89.1 11.44 1 NA 0 0
#> 51.2 18.23 1 83 0 1
#> 15 22.68 1 48 0 0
#> 68.2 20.62 1 44 0 0
#> 66 22.13 1 53 0 0
#> 86.1 23.81 1 58 0 1
#> 60.1 13.15 1 38 1 0
#> 36 21.19 1 48 0 1
#> 130.1 16.47 1 53 0 1
#> 86.2 23.81 1 58 0 1
#> 37 12.52 1 57 1 0
#> 14 12.89 1 21 0 0
#> 61.1 10.12 1 36 0 1
#> 16.1 8.71 1 71 0 1
#> 42 12.43 1 49 0 1
#> 197.1 21.60 1 69 1 0
#> 189 10.51 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 183.1 9.24 1 67 1 0
#> 149 8.37 1 33 1 0
#> 39 15.59 1 37 0 1
#> 91.1 5.33 1 61 0 1
#> 52.2 10.42 1 52 0 1
#> 14.1 12.89 1 21 0 0
#> 180 14.82 1 37 0 0
#> 107.1 11.18 1 54 1 0
#> 36.1 21.19 1 48 0 1
#> 76 19.22 1 54 0 1
#> 32 20.90 1 37 1 0
#> 192.3 16.44 1 31 1 0
#> 99 21.19 1 38 0 1
#> 169.1 22.41 1 46 0 0
#> 139.1 21.49 1 63 1 0
#> 199 19.81 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 45.1 17.42 1 54 0 1
#> 99.1 21.19 1 38 0 1
#> 108.1 18.29 1 39 0 1
#> 36.2 21.19 1 48 0 1
#> 56.2 12.21 1 60 0 0
#> 113 22.86 1 34 0 0
#> 57.1 14.46 1 45 0 1
#> 164.2 23.60 1 76 0 1
#> 114 13.68 1 NA 0 0
#> 167 15.55 1 56 1 0
#> 114.1 13.68 1 NA 0 0
#> 42.1 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 36.3 21.19 1 48 0 1
#> 41.1 18.02 1 40 1 0
#> 123.1 13.00 1 44 1 0
#> 195 11.76 1 NA 1 0
#> 183.2 9.24 1 67 1 0
#> 92 22.92 1 47 0 1
#> 22 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 102 24.00 0 49 0 0
#> 182 24.00 0 35 0 0
#> 151 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 7 24.00 0 37 1 0
#> 38 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 126 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 22.1 24.00 0 52 1 0
#> 116 24.00 0 58 0 1
#> 11 24.00 0 42 0 1
#> 103 24.00 0 56 1 0
#> 176 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 19 24.00 0 57 0 1
#> 151.1 24.00 0 42 0 0
#> 102.1 24.00 0 49 0 0
#> 44 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 19.1 24.00 0 57 0 1
#> 193 24.00 0 45 0 1
#> 115 24.00 0 NA 1 0
#> 147 24.00 0 76 1 0
#> 67 24.00 0 25 0 0
#> 22.2 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 142 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 160.1 24.00 0 31 1 0
#> 151.2 24.00 0 42 0 0
#> 138 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 27 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 147.1 24.00 0 76 1 0
#> 48.1 24.00 0 31 1 0
#> 147.2 24.00 0 76 1 0
#> 72 24.00 0 40 0 1
#> 19.2 24.00 0 57 0 1
#> 146 24.00 0 63 1 0
#> 72.1 24.00 0 40 0 1
#> 196 24.00 0 19 0 0
#> 31.2 24.00 0 36 0 1
#> 20.1 24.00 0 46 1 0
#> 138.1 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 38.1 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 54 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 20.2 24.00 0 46 1 0
#> 71.1 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 173.2 24.00 0 19 0 1
#> 138.2 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 38.2 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 20.3 24.00 0 46 1 0
#> 144 24.00 0 28 0 1
#> 116.1 24.00 0 58 0 1
#> 7.1 24.00 0 37 1 0
#> 94 24.00 0 51 0 1
#> 160.2 24.00 0 31 1 0
#> 142.1 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 173.3 24.00 0 19 0 1
#> 193.1 24.00 0 45 0 1
#> 87 24.00 0 27 0 0
#> 83.2 24.00 0 6 0 0
#> 138.3 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#> 3.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.68 NA NA NA
#> 2 age, Cure model 0.0341 NA NA NA
#> 3 grade_ii, Cure model -0.107 NA NA NA
#> 4 grade_iii, Cure model 0.789 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0177 NA NA NA
#> 2 grade_ii, Survival model 0.510 NA NA NA
#> 3 grade_iii, Survival model 0.0693 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.67807 0.03411 -0.10674 0.78858
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 239.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.67806873 0.03411394 -0.10674047 0.78857694
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01768066 0.51038616 0.06928135
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.994838e-01 1.000629e-01 3.332703e-01 4.725798e-01 7.011071e-02
#> [6] 9.353572e-02 2.264479e-01 8.046190e-01 9.812557e-01 6.434309e-01
#> [11] 4.195221e-01 8.554428e-01 1.442391e-01 9.685036e-04 1.068808e-01
#> [16] 1.610306e-02 1.969455e-01 5.983549e-01 9.685036e-04 2.994838e-01
#> [21] 6.900769e-01 4.456942e-01 3.591041e-05 9.445705e-01 1.287757e-01
#> [26] 2.368369e-01 2.582244e-01 2.582244e-01 6.900769e-01 2.968211e-02
#> [31] 3.814144e-01 1.698156e-01 9.084538e-01 2.582244e-01 5.983549e-01
#> [36] 1.212300e-01 3.450279e-01 1.442391e-01 4.843510e-04 4.996958e-01
#> [41] 3.217778e-01 2.247207e-02 7.381109e-01 2.065747e-01 6.589278e-01
#> [46] 1.101321e-02 9.264969e-01 7.878395e-01 7.577582e-02 7.577582e-02
#> [51] 4.066470e-01 1.876562e-01 1.442391e-01 8.764055e-03 7.577582e-02
#> [56] 1.912649e-02 3.591041e-05 4.725798e-01 3.779061e-02 2.368369e-01
#> [61] 3.591041e-05 5.550796e-01 5.271620e-01 7.381109e-01 8.554428e-01
#> [66] 5.693611e-01 2.247207e-02 3.606379e-03 8.046190e-01 8.906485e-01
#> [71] 3.569853e-01 9.445705e-01 6.900769e-01 5.271620e-01 3.939337e-01
#> [76] 6.589278e-01 3.779061e-02 1.139227e-01 6.453908e-02 2.582244e-01
#> [81] 3.779061e-02 1.101321e-02 2.968211e-02 7.711184e-01 2.065747e-01
#> [86] 3.779061e-02 1.287757e-01 3.779061e-02 5.983549e-01 6.803712e-03
#> [91] 4.195221e-01 9.685036e-04 3.691229e-01 5.693611e-01 4.456942e-01
#> [96] 3.779061e-02 1.698156e-01 4.996958e-01 8.046190e-01 5.070669e-03
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 5 105 100 60 190 128 171 183 127 49 57 16 51
#> 16.43 19.75 16.07 13.15 20.81 20.35 16.57 9.24 3.53 12.19 14.46 8.71 18.23
#> 164 58 194 30 56 164.1 5.1 52 81 86 91 108 130
#> 23.60 19.34 22.40 17.43 12.21 23.60 16.43 10.42 14.06 23.81 5.33 18.29 16.47
#> 192 192.1 52.1 139 157 41 77 192.2 56.1 179 125 51.1 168
#> 16.44 16.44 10.42 21.49 15.10 18.02 7.27 16.44 12.21 18.63 15.65 18.23 23.72
#> 123 79 197 61 45 107 169 25 187 68 68.1 96 117
#> 13.00 16.23 21.60 10.12 17.42 11.18 22.41 6.32 9.92 20.62 20.62 14.54 17.46
#> 51.2 15 68.2 66 86.1 60.1 36 130.1 86.2 37 14 61.1 16.1
#> 18.23 22.68 20.62 22.13 23.81 13.15 21.19 16.47 23.81 12.52 12.89 10.12 8.71
#> 42 197.1 129 183.1 149 39 91.1 52.2 14.1 180 107.1 36.1 76
#> 12.43 21.60 23.41 9.24 8.37 15.59 5.33 10.42 12.89 14.82 11.18 21.19 19.22
#> 32 192.3 99 169.1 139.1 101 45.1 99.1 108.1 36.2 56.2 113 57.1
#> 20.90 16.44 21.19 22.41 21.49 9.97 17.42 21.19 18.29 21.19 12.21 22.86 14.46
#> 164.2 167 42.1 81.1 36.3 41.1 123.1 183.2 92 22 152 83 102
#> 23.60 15.55 12.43 14.06 21.19 18.02 13.00 9.24 22.92 24.00 24.00 24.00 24.00
#> 182 151 31 160 3 118 109 173 7 38 20 126 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 116 11 103 176 2 19 151.1 102.1 44 162 19.1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 67 22.2 186 142 178 160.1 151.2 138 48 83.1 27 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 147.1 48.1 147.2 72 19.2 146 72.1 196 31.2 20.1 138.1 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 38.1 173.1 54 82 20.2 71.1 172 173.2 138.2 162.1 17 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.2 12 20.3 144 116.1 7.1 94 160.2 142.1 104 173.3 193.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.2 138.3 9 87.1 3.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[63]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01802348 0.70653512 0.53381395
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.73129323 0.02006477 -0.19492136
#> grade_iii, Cure model
#> 0.07147253
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 139 21.49 1 63 1 0
#> 187 9.92 1 39 1 0
#> 76 19.22 1 54 0 1
#> 100 16.07 1 60 0 0
#> 113 22.86 1 34 0 0
#> 153 21.33 1 55 1 0
#> 123 13.00 1 44 1 0
#> 188 16.16 1 46 0 1
#> 134 17.81 1 47 1 0
#> 41 18.02 1 40 1 0
#> 57 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 36 21.19 1 48 0 1
#> 36.1 21.19 1 48 0 1
#> 130 16.47 1 53 0 1
#> 88 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 55 19.34 1 69 0 1
#> 55.1 19.34 1 69 0 1
#> 59 10.16 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 40 18.00 1 28 1 0
#> 51 18.23 1 83 0 1
#> 61 10.12 1 36 0 1
#> 96 14.54 1 33 0 1
#> 78 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 140 12.68 1 59 1 0
#> 89 11.44 1 NA 0 0
#> 187.1 9.92 1 39 1 0
#> 184 17.77 1 38 0 0
#> 66 22.13 1 53 0 0
#> 86.1 23.81 1 58 0 1
#> 100.1 16.07 1 60 0 0
#> 85 16.44 1 36 0 0
#> 30 17.43 1 78 0 0
#> 180 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 36.2 21.19 1 48 0 1
#> 14.1 12.89 1 21 0 0
#> 139.1 21.49 1 63 1 0
#> 170 19.54 1 43 0 1
#> 96.1 14.54 1 33 0 1
#> 57.1 14.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 63 22.77 1 31 1 0
#> 66.1 22.13 1 53 0 0
#> 159 10.55 1 50 0 1
#> 37 12.52 1 57 1 0
#> 79 16.23 1 54 1 0
#> 111.1 17.45 1 47 0 1
#> 70 7.38 1 30 1 0
#> 56 12.21 1 60 0 0
#> 100.2 16.07 1 60 0 0
#> 24 23.89 1 38 0 0
#> 13 14.34 1 54 0 1
#> 128 20.35 1 35 0 1
#> 124 9.73 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 184.1 17.77 1 38 0 0
#> 66.2 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 175 21.91 1 43 0 0
#> 192 16.44 1 31 1 0
#> 15 22.68 1 48 0 0
#> 133 14.65 1 57 0 0
#> 129 23.41 1 53 1 0
#> 154 12.63 1 20 1 0
#> 107 11.18 1 54 1 0
#> 136 21.83 1 43 0 1
#> 51.1 18.23 1 83 0 1
#> 61.1 10.12 1 36 0 1
#> 10 10.53 1 34 0 0
#> 76.1 19.22 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 129.1 23.41 1 53 1 0
#> 55.2 19.34 1 69 0 1
#> 180.1 14.82 1 37 0 0
#> 42 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 189 10.51 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 168 23.72 1 70 0 0
#> 49.1 12.19 1 48 1 0
#> 36.3 21.19 1 48 0 1
#> 164 23.60 1 76 0 1
#> 108 18.29 1 39 0 1
#> 187.2 9.92 1 39 1 0
#> 180.2 14.82 1 37 0 0
#> 169 22.41 1 46 0 0
#> 29 15.45 1 68 1 0
#> 57.2 14.46 1 45 0 1
#> 59.1 10.16 1 NA 1 0
#> 139.2 21.49 1 63 1 0
#> 194 22.40 1 38 0 1
#> 78.1 23.88 1 43 0 0
#> 168.1 23.72 1 70 0 0
#> 169.1 22.41 1 46 0 0
#> 111.2 17.45 1 47 0 1
#> 49.2 12.19 1 48 1 0
#> 18 15.21 1 49 1 0
#> 124.1 9.73 1 NA 1 0
#> 36.4 21.19 1 48 0 1
#> 166 19.98 1 48 0 0
#> 125 15.65 1 67 1 0
#> 10.1 10.53 1 34 0 0
#> 50.1 10.02 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 113.1 22.86 1 34 0 0
#> 106 16.67 1 49 1 0
#> 139.3 21.49 1 63 1 0
#> 33 24.00 0 53 0 0
#> 196 24.00 0 19 0 0
#> 94 24.00 0 51 0 1
#> 141 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 9 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 152 24.00 0 36 0 1
#> 20 24.00 0 46 1 0
#> 165 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 193 24.00 0 45 0 1
#> 53.1 24.00 0 32 0 1
#> 198 24.00 0 66 0 1
#> 118 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 54 24.00 0 53 1 0
#> 144 24.00 0 28 0 1
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 135 24.00 0 58 1 0
#> 47 24.00 0 38 0 1
#> 152.1 24.00 0 36 0 1
#> 196.1 24.00 0 19 0 0
#> 186 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 11 24.00 0 42 0 1
#> 118.1 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 53.2 24.00 0 32 0 1
#> 173 24.00 0 19 0 1
#> 121 24.00 0 57 1 0
#> 94.1 24.00 0 51 0 1
#> 163 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 178 24.00 0 52 1 0
#> 38.1 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 84 24.00 0 39 0 1
#> 147 24.00 0 76 1 0
#> 152.2 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 138.1 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 135.1 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 198.1 24.00 0 66 0 1
#> 152.3 24.00 0 36 0 1
#> 152.4 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 138.2 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 109 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 46.1 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 121.1 24.00 0 57 1 0
#> 9.1 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 152.5 24.00 0 36 0 1
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 118.2 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 152.6 24.00 0 36 0 1
#> 176.1 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 142.1 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 144.1 24.00 0 28 0 1
#> 65 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 142.2 24.00 0 53 0 0
#> 198.2 24.00 0 66 0 1
#> 174 24.00 0 49 1 0
#> 142.3 24.00 0 53 0 0
#> 151.1 24.00 0 42 0 0
#> 72.1 24.00 0 40 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.731 NA NA NA
#> 2 age, Cure model 0.0201 NA NA NA
#> 3 grade_ii, Cure model -0.195 NA NA NA
#> 4 grade_iii, Cure model 0.0715 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0180 NA NA NA
#> 2 grade_ii, Survival model 0.707 NA NA NA
#> 3 grade_iii, Survival model 0.534 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73129 0.02006 -0.19492 0.07147
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 258.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73129323 0.02006477 -0.19492136 0.07147253
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01802348 0.70653512 0.53381395
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 8.538882e-02 9.286340e-01 2.335465e-01 4.650413e-01 2.176072e-02
#> [6] 1.123309e-01 6.925914e-01 4.535113e-01 3.125282e-01 2.920585e-01
#> [11] 6.397527e-01 1.643122e-01 1.198985e-01 1.198985e-01 3.971826e-01
#> [16] 2.522938e-01 5.497498e-01 2.067471e-01 2.067471e-01 2.800121e-03
#> [21] 3.023321e-01 2.718827e-01 9.000383e-01 6.136286e-01 6.884508e-04
#> [26] 7.060902e-01 7.331527e-01 9.286340e-01 3.227682e-01 5.432415e-02
#> [31] 2.800121e-03 4.650413e-01 4.083832e-01 3.750479e-01 5.623319e-01
#> [36] 4.306692e-01 1.198985e-01 7.060902e-01 8.538882e-02 1.980022e-01
#> [41] 6.136286e-01 6.397527e-01 3.435675e-01 2.994009e-02 5.432415e-02
#> [46] 8.573878e-01 7.605196e-01 4.420557e-01 3.435675e-01 9.711890e-01
#> [51] 7.879895e-01 4.650413e-01 9.471626e-05 6.791144e-01 1.808999e-01
#> [56] 9.855479e-01 3.227682e-01 5.432415e-02 8.019213e-01 7.183926e-02
#> [61] 4.083832e-01 3.425529e-02 6.004580e-01 1.479535e-02 7.468880e-01
#> [66] 8.433060e-01 7.855129e-02 2.718827e-01 9.000383e-01 8.715410e-01
#> [71] 2.335465e-01 1.479535e-02 2.067471e-01 5.623319e-01 7.742187e-01
#> [76] 5.127006e-01 1.561477e-01 5.999410e-03 8.019213e-01 1.198985e-01
#> [81] 1.122803e-02 2.620598e-01 9.286340e-01 5.623319e-01 3.891037e-02
#> [86] 5.249569e-01 6.397527e-01 8.538882e-02 4.893990e-02 6.884508e-04
#> [91] 5.999410e-03 3.891037e-02 3.435675e-01 8.019213e-01 5.373302e-01
#> [96] 1.198985e-01 1.893393e-01 5.004806e-01 8.715410e-01 1.724969e-01
#> [101] 2.176072e-02 3.860896e-01 8.538882e-02 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 139 187 76 100 113 153 123 188 134 41 57 190 36
#> 21.49 9.92 19.22 16.07 22.86 21.33 13.00 16.16 17.81 18.02 14.46 20.81 21.19
#> 36.1 130 88 157 55 55.1 86 40 51 61 96 78 14
#> 21.19 16.47 18.37 15.10 19.34 19.34 23.81 18.00 18.23 10.12 14.54 23.88 12.89
#> 140 187.1 184 66 86.1 100.1 85 30 180 5 36.2 14.1 139.1
#> 12.68 9.92 17.77 22.13 23.81 16.07 16.44 17.43 14.82 16.43 21.19 12.89 21.49
#> 170 96.1 57.1 111 63 66.1 159 37 79 111.1 70 56 100.2
#> 19.54 14.54 14.46 17.45 22.77 22.13 10.55 12.52 16.23 17.45 7.38 12.21 16.07
#> 24 13 128 127 184.1 66.2 49 175 192 15 133 129 154
#> 23.89 14.34 20.35 3.53 17.77 22.13 12.19 21.91 16.44 22.68 14.65 23.41 12.63
#> 107 136 51.1 61.1 10 76.1 129.1 55.2 180.1 42 39 90 168
#> 11.18 21.83 18.23 10.12 10.53 19.22 23.41 19.34 14.82 12.43 15.59 20.94 23.72
#> 49.1 36.3 164 108 187.2 180.2 169 29 57.2 139.2 194 78.1 168.1
#> 12.19 21.19 23.60 18.29 9.92 14.82 22.41 15.45 14.46 21.49 22.40 23.88 23.72
#> 169.1 111.2 49.2 18 36.4 166 125 10.1 68 113.1 106 139.3 33
#> 22.41 17.45 12.19 15.21 21.19 19.98 15.65 10.53 20.62 22.86 16.67 21.49 24.00
#> 196 94 141 95 112 9 75 152 20 165 38 185 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 193 53.1 198 118 54 144 132 67 135 47 152.1 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 31 11 118.1 46 53.2 173 121 94.1 163 138 161 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 131 173.1 84 147 152.2 28 12 138.1 119 135.1 156 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 152.3 152.4 176 138.2 47.1 109 142 148 46.1 21 121.1 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 152.5 72 151 118.2 22 152.6 176.1 2 142.1 162 163.1 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 83 142.2 198.2 174 142.3 151.1 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[64]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005776744 0.343667651 0.486777296
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.056165752 -0.007562484 0.831653057
#> grade_iii, Cure model
#> 1.111069609
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 57 14.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 66 22.13 1 53 0 0
#> 167 15.55 1 56 1 0
#> 167.1 15.55 1 56 1 0
#> 56 12.21 1 60 0 0
#> 55 19.34 1 69 0 1
#> 153 21.33 1 55 1 0
#> 77 7.27 1 67 0 1
#> 63 22.77 1 31 1 0
#> 25 6.32 1 34 1 0
#> 127 3.53 1 62 0 1
#> 79 16.23 1 54 1 0
#> 68 20.62 1 44 0 0
#> 56.1 12.21 1 60 0 0
#> 117 17.46 1 26 0 1
#> 127.1 3.53 1 62 0 1
#> 129 23.41 1 53 1 0
#> 23 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 110 17.56 1 65 0 1
#> 57.1 14.46 1 45 0 1
#> 78 23.88 1 43 0 0
#> 69 23.23 1 25 0 1
#> 154 12.63 1 20 1 0
#> 155 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 18 15.21 1 49 1 0
#> 139.1 21.49 1 63 1 0
#> 170 19.54 1 43 0 1
#> 133 14.65 1 57 0 0
#> 92 22.92 1 47 0 1
#> 128 20.35 1 35 0 1
#> 101 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 63.1 22.77 1 31 1 0
#> 155.1 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 149 8.37 1 33 1 0
#> 36 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 129.1 23.41 1 53 1 0
#> 56.2 12.21 1 60 0 0
#> 167.2 15.55 1 56 1 0
#> 89 11.44 1 NA 0 0
#> 41.1 18.02 1 40 1 0
#> 169 22.41 1 46 0 0
#> 128.1 20.35 1 35 0 1
#> 42 12.43 1 49 0 1
#> 49 12.19 1 48 1 0
#> 15 22.68 1 48 0 0
#> 60 13.15 1 38 1 0
#> 32 20.90 1 37 1 0
#> 179 18.63 1 42 0 0
#> 136 21.83 1 43 0 1
#> 101.1 9.97 1 10 0 1
#> 70 7.38 1 30 1 0
#> 50 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 63.2 22.77 1 31 1 0
#> 18.1 15.21 1 49 1 0
#> 167.3 15.55 1 56 1 0
#> 85 16.44 1 36 0 0
#> 23.1 16.92 1 61 0 0
#> 111 17.45 1 47 0 1
#> 149.1 8.37 1 33 1 0
#> 91 5.33 1 61 0 1
#> 128.2 20.35 1 35 0 1
#> 155.2 13.08 1 26 0 0
#> 107 11.18 1 54 1 0
#> 129.2 23.41 1 53 1 0
#> 69.1 23.23 1 25 0 1
#> 124 9.73 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 56.3 12.21 1 60 0 0
#> 24 23.89 1 38 0 0
#> 50.1 10.02 1 NA 1 0
#> 92.1 22.92 1 47 0 1
#> 91.1 5.33 1 61 0 1
#> 134 17.81 1 47 1 0
#> 5 16.43 1 51 0 1
#> 76.1 19.22 1 54 0 1
#> 5.1 16.43 1 51 0 1
#> 159 10.55 1 50 0 1
#> 125 15.65 1 67 1 0
#> 140 12.68 1 59 1 0
#> 68.1 20.62 1 44 0 0
#> 192 16.44 1 31 1 0
#> 166 19.98 1 48 0 0
#> 56.4 12.21 1 60 0 0
#> 134.1 17.81 1 47 1 0
#> 78.1 23.88 1 43 0 0
#> 41.2 18.02 1 40 1 0
#> 41.3 18.02 1 40 1 0
#> 129.3 23.41 1 53 1 0
#> 51 18.23 1 83 0 1
#> 85.1 16.44 1 36 0 0
#> 123 13.00 1 44 1 0
#> 124.1 9.73 1 NA 1 0
#> 179.1 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 110.1 17.56 1 65 0 1
#> 127.2 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 106 16.67 1 49 1 0
#> 108 18.29 1 39 0 1
#> 197 21.60 1 69 1 0
#> 42.1 12.43 1 49 0 1
#> 134.2 17.81 1 47 1 0
#> 3 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 193 24.00 0 45 0 1
#> 65 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 64.1 24.00 0 43 0 0
#> 84 24.00 0 39 0 1
#> 147 24.00 0 76 1 0
#> 132 24.00 0 55 0 0
#> 46 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 104 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 112 24.00 0 61 0 0
#> 62.1 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 142 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 131 24.00 0 66 0 0
#> 193.1 24.00 0 45 0 1
#> 160 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 109 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 87 24.00 0 27 0 0
#> 131.1 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 19 24.00 0 57 0 1
#> 22.1 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 178 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 46.1 24.00 0 71 0 0
#> 147.1 24.00 0 76 1 0
#> 119 24.00 0 17 0 0
#> 185 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 82 24.00 0 34 0 0
#> 178.1 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 148 24.00 0 61 1 0
#> 9 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 182 24.00 0 35 0 0
#> 7 24.00 0 37 1 0
#> 75 24.00 0 21 1 0
#> 64.2 24.00 0 43 0 0
#> 122 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 62.2 24.00 0 71 0 0
#> 22.2 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 47 24.00 0 38 0 1
#> 38.1 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 132.1 24.00 0 55 0 0
#> 84.1 24.00 0 39 0 1
#> 82.1 24.00 0 34 0 0
#> 161 24.00 0 45 0 0
#> 17.1 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 162.1 24.00 0 51 0 0
#> 147.2 24.00 0 76 1 0
#> 109.1 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 83 24.00 0 6 0 0
#> 19.2 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0562 NA NA NA
#> 2 age, Cure model -0.00756 NA NA NA
#> 3 grade_ii, Cure model 0.832 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00578 NA NA NA
#> 2 grade_ii, Survival model 0.344 NA NA NA
#> 3 grade_iii, Survival model 0.487 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.056166 -0.007562 0.831653 1.111070
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.056165752 -0.007562484 0.831653057 1.111069609
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005776744 0.343667651 0.486777296
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.55539826 0.80897461 0.41206662 0.37652565 0.76564129 0.76564129
#> [7] 0.88002877 0.54677605 0.43346715 0.96329341 0.31500077 0.96867318
#> [13] 0.98456713 0.75261370 0.48343288 0.88002877 0.67781465 0.98456713
#> [19] 0.17845175 0.69191182 0.44405475 0.66357739 0.80897461 0.08743548
#> [25] 0.24292521 0.86265285 0.83307384 0.94152886 0.79046117 0.41206662
#> [31] 0.53795580 0.80279992 0.27377615 0.50234812 0.93053663 0.14780821
#> [37] 0.31500077 0.83307384 0.82107264 0.94701649 0.44405475 0.60431102
#> [43] 0.17845175 0.88002877 0.76564129 0.60431102 0.36414047 0.50234812
#> [49] 0.86851790 0.90814717 0.35162579 0.82708971 0.47377044 0.57188777
#> [55] 0.38876664 0.93053663 0.95787136 0.46395871 0.31500077 0.79046117
#> [61] 0.76564129 0.71944130 0.69191182 0.68490438 0.94701649 0.97403164
#> [67] 0.50234812 0.83307384 0.91381125 0.17845175 0.24292521 0.91381125
#> [73] 0.65620245 0.88002877 0.03917325 0.27377615 0.97403164 0.63426554
#> [79] 0.73947751 0.55539826 0.73947751 0.92497650 0.75915758 0.85676447
#> [85] 0.48343288 0.71944130 0.52897568 0.88002877 0.63426554 0.08743548
#> [91] 0.60431102 0.60431102 0.17845175 0.59636745 0.71944130 0.85083604
#> [97] 0.57188777 0.71262622 0.66357739 0.98456713 0.30113532 0.70573802
#> [103] 0.58824780 0.40060301 0.86851790 0.63426554 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 76 57 139 66 167 167.1 56 55 153 77 63 25 127
#> 19.22 14.46 21.49 22.13 15.55 15.55 12.21 19.34 21.33 7.27 22.77 6.32 3.53
#> 79 68 56.1 117 127.1 129 23 99 110 57.1 78 69 154
#> 16.23 20.62 12.21 17.46 3.53 23.41 16.92 21.19 17.56 14.46 23.88 23.23 12.63
#> 155 187 18 139.1 170 133 92 128 101 168 63.1 155.1 13
#> 13.08 9.92 15.21 21.49 19.54 14.65 22.92 20.35 9.97 23.72 22.77 13.08 14.34
#> 149 36 41 129.1 56.2 167.2 41.1 169 128.1 42 49 15 60
#> 8.37 21.19 18.02 23.41 12.21 15.55 18.02 22.41 20.35 12.43 12.19 22.68 13.15
#> 32 179 136 101.1 70 90 63.2 18.1 167.3 85 23.1 111 149.1
#> 20.90 18.63 21.83 9.97 7.38 20.94 22.77 15.21 15.55 16.44 16.92 17.45 8.37
#> 91 128.2 155.2 107 129.2 69.1 107.1 184 56.3 24 92.1 91.1 134
#> 5.33 20.35 13.08 11.18 23.41 23.23 11.18 17.77 12.21 23.89 22.92 5.33 17.81
#> 5 76.1 5.1 159 125 140 68.1 192 166 56.4 134.1 78.1 41.2
#> 16.43 19.22 16.43 10.55 15.65 12.68 20.62 16.44 19.98 12.21 17.81 23.88 18.02
#> 41.3 129.3 51 85.1 123 179.1 181 110.1 127.2 113 106 108 197
#> 18.02 23.41 18.23 16.44 13.00 18.63 16.46 17.56 3.53 22.86 16.67 18.29 21.60
#> 42.1 134.2 3 3.1 33 34 193 65 64 64.1 84 147 132
#> 12.43 17.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 22 2 48 163 176 104 162 38 71 126 62 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 44 142 116 131 193.1 160 21 138 142.1 33.1 109 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 87 131.1 67 19 22.1 121 72 178 95 46.1 147.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 102 146 135 82 178.1 17 120 12 148 9 103 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 75 64.2 122 54 62.2 22.2 95.1 47 38.1 19.1 132.1 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 161 17.1 74 80 162.1 147.2 109.1 144 83 19.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[65]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01646567 0.32745178 0.24565416
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.14227126 0.01962846 -0.04612025
#> grade_iii, Cure model
#> 1.10829982
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 25 6.32 1 34 1 0
#> 68 20.62 1 44 0 0
#> 199 19.81 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 79 16.23 1 54 1 0
#> 86 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 49 12.19 1 48 1 0
#> 92 22.92 1 47 0 1
#> 127 3.53 1 62 0 1
#> 59 10.16 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 108 18.29 1 39 0 1
#> 111 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 99 21.19 1 38 0 1
#> 159 10.55 1 50 0 1
#> 70 7.38 1 30 1 0
#> 90 20.94 1 50 0 1
#> 167 15.55 1 56 1 0
#> 123 13.00 1 44 1 0
#> 129 23.41 1 53 1 0
#> 124 9.73 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 15 22.68 1 48 0 0
#> 13 14.34 1 54 0 1
#> 145 10.07 1 65 1 0
#> 92.1 22.92 1 47 0 1
#> 111.1 17.45 1 47 0 1
#> 63 22.77 1 31 1 0
#> 129.1 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 89 11.44 1 NA 0 0
#> 189 10.51 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 192 16.44 1 31 1 0
#> 55 19.34 1 69 0 1
#> 23 16.92 1 61 0 0
#> 175 21.91 1 43 0 0
#> 101 9.97 1 10 0 1
#> 139 21.49 1 63 1 0
#> 111.2 17.45 1 47 0 1
#> 169 22.41 1 46 0 0
#> 194 22.40 1 38 0 1
#> 100 16.07 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 106 16.67 1 49 1 0
#> 133 14.65 1 57 0 0
#> 8 18.43 1 32 0 0
#> 13.1 14.34 1 54 0 1
#> 192.1 16.44 1 31 1 0
#> 66 22.13 1 53 0 0
#> 127.1 3.53 1 62 0 1
#> 199.1 19.81 1 NA 0 1
#> 50 10.02 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 89.1 11.44 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 77.1 7.27 1 67 0 1
#> 180 14.82 1 37 0 0
#> 157 15.10 1 47 0 0
#> 183 9.24 1 67 1 0
#> 130 16.47 1 53 0 1
#> 97.1 19.14 1 65 0 1
#> 139.1 21.49 1 63 1 0
#> 4 17.64 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 180.1 14.82 1 37 0 0
#> 170 19.54 1 43 0 1
#> 179 18.63 1 42 0 0
#> 39 15.59 1 37 0 1
#> 14 12.89 1 21 0 0
#> 29 15.45 1 68 1 0
#> 177 12.53 1 75 0 0
#> 29.1 15.45 1 68 1 0
#> 5 16.43 1 51 0 1
#> 15.1 22.68 1 48 0 0
#> 158 20.14 1 74 1 0
#> 101.1 9.97 1 10 0 1
#> 139.2 21.49 1 63 1 0
#> 70.1 7.38 1 30 1 0
#> 59.1 10.16 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 189.1 10.51 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 96.1 14.54 1 33 0 1
#> 6 15.64 1 39 0 0
#> 57 14.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 113 22.86 1 34 0 0
#> 59.2 10.16 1 NA 1 0
#> 197.1 21.60 1 69 1 0
#> 105 19.75 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 6.1 15.64 1 39 0 0
#> 195 11.76 1 NA 1 0
#> 96.2 14.54 1 33 0 1
#> 88 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 41 18.02 1 40 1 0
#> 164 23.60 1 76 0 1
#> 39.1 15.59 1 37 0 1
#> 125 15.65 1 67 1 0
#> 68.1 20.62 1 44 0 0
#> 60 13.15 1 38 1 0
#> 194.1 22.40 1 38 0 1
#> 96.3 14.54 1 33 0 1
#> 89.2 11.44 1 NA 0 0
#> 195.1 11.76 1 NA 1 0
#> 20 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 196 24.00 0 19 0 0
#> 143 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 28 24.00 0 67 1 0
#> 147 24.00 0 76 1 0
#> 142 24.00 0 53 0 0
#> 20.1 24.00 0 46 1 0
#> 160 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 152 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 109 24.00 0 48 0 0
#> 162 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 9 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 147.1 24.00 0 76 1 0
#> 144 24.00 0 28 0 1
#> 28.1 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 151 24.00 0 42 0 0
#> 142.1 24.00 0 53 0 0
#> 182.2 24.00 0 35 0 0
#> 44 24.00 0 56 0 0
#> 12 24.00 0 63 0 0
#> 28.2 24.00 0 67 1 0
#> 28.3 24.00 0 67 1 0
#> 31 24.00 0 36 0 1
#> 147.2 24.00 0 76 1 0
#> 17 24.00 0 38 0 1
#> 141.1 24.00 0 44 1 0
#> 102.1 24.00 0 49 0 0
#> 152.1 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 182.3 24.00 0 35 0 0
#> 116 24.00 0 58 0 1
#> 109.1 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 47 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 94 24.00 0 51 0 1
#> 122 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 38 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 156 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 147.3 24.00 0 76 1 0
#> 162.1 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 20.2 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 27 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 173.1 24.00 0 19 0 1
#> 1 24.00 0 23 1 0
#> 196.1 24.00 0 19 0 0
#> 148 24.00 0 61 1 0
#> 1.1 24.00 0 23 1 0
#> 46 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#> 156.1 24.00 0 50 1 0
#> 27.1 24.00 0 63 1 0
#> 142.2 24.00 0 53 0 0
#> 144.1 24.00 0 28 0 1
#> 115.1 24.00 0 NA 1 0
#> 102.2 24.00 0 49 0 0
#> 174 24.00 0 49 1 0
#> 47.1 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 119 24.00 0 17 0 0
#> 152.2 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.14 NA NA NA
#> 2 age, Cure model 0.0196 NA NA NA
#> 3 grade_ii, Cure model -0.0461 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0165 NA NA NA
#> 2 grade_ii, Survival model 0.327 NA NA NA
#> 3 grade_iii, Survival model 0.246 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.14227 0.01963 -0.04612 1.10830
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 250.3
#> Residual Deviance: 236.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.14227126 0.01962846 -0.04612025 1.10829982
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01646567 0.32745178 0.24565416
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.594985e-01 9.459167e-01 8.642132e-02 9.922587e-02 3.560332e-01
#> [6] 3.535246e-05 5.422191e-01 7.410090e-01 5.143048e-03 9.638159e-01
#> [11] 2.654394e-01 2.148007e-01 2.348730e-01 9.105944e-01 6.840940e-02
#> [16] 7.575101e-01 8.760439e-01 7.422795e-02 4.446103e-01 6.766704e-01
#> [21] 2.182279e-03 1.129900e-01 1.423019e-02 6.300913e-01 7.909961e-01
#> [26] 5.143048e-03 2.348730e-01 1.161112e-02 2.182279e-03 8.025389e-02
#> [31] 1.681495e-01 3.100446e-01 1.355112e-01 2.762515e-01 3.455614e-02
#> [36] 8.080117e-01 5.278042e-02 2.348730e-01 2.006123e-02 2.351659e-02
#> [41] 3.681391e-01 4.329129e-02 2.873386e-01 5.275970e-01 1.954007e-01
#> [46] 6.300913e-01 3.100446e-01 3.053256e-02 9.638159e-01 1.355112e-01
#> [51] 7.246430e-01 9.105944e-01 4.992301e-01 4.852082e-01 8.415666e-01
#> [56] 2.985910e-01 1.681495e-01 5.278042e-02 2.698987e-04 4.992301e-01
#> [61] 1.277963e-01 1.860129e-01 4.186041e-01 6.925041e-01 4.579873e-01
#> [66] 7.084443e-01 4.579873e-01 3.441017e-01 1.423019e-02 1.059762e-01
#> [71] 8.080117e-01 5.278042e-02 8.760439e-01 7.741704e-01 3.883267e-02
#> [76] 5.422191e-01 3.930816e-01 5.999269e-01 3.100446e-01 9.089130e-03
#> [81] 4.329129e-02 1.202502e-01 5.999269e-01 3.930816e-01 5.422191e-01
#> [86] 2.049770e-01 8.587010e-01 1.355112e-01 2.247736e-01 9.307695e-04
#> [91] 4.186041e-01 3.805000e-01 8.642132e-02 6.609572e-01 2.351659e-02
#> [96] 5.422191e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00
#>
#> $Time
#> 76 25 68 128 79 86 96 49 92 127 45 108 111
#> 19.22 6.32 20.62 20.35 16.23 23.81 14.54 12.19 22.92 3.53 17.42 18.29 17.45
#> 77 99 159 70 90 167 123 129 166 15 13 145 92.1
#> 7.27 21.19 10.55 7.38 20.94 15.55 13.00 23.41 19.98 22.68 14.34 10.07 22.92
#> 111.1 63 129.1 190 97 192 55 23 175 101 139 111.2 169
#> 17.45 22.77 23.41 20.81 19.14 16.44 19.34 16.92 21.91 9.97 21.49 17.45 22.41
#> 194 100 197 106 133 8 13.1 192.1 66 127.1 55.1 37 77.1
#> 22.40 16.07 21.60 16.67 14.65 18.43 14.34 16.44 22.13 3.53 19.34 12.52 7.27
#> 180 157 183 130 97.1 139.1 168 180.1 170 179 39 14 29
#> 14.82 15.10 9.24 16.47 19.14 21.49 23.72 14.82 19.54 18.63 15.59 12.89 15.45
#> 177 29.1 5 15.1 158 101.1 139.2 70.1 93 136 96.1 6 57
#> 12.53 15.45 16.43 22.68 20.14 9.97 21.49 7.38 10.33 21.83 14.54 15.64 14.46
#> 85 113 197.1 105 57.1 6.1 96.2 88 16 58 41 164 39.1
#> 16.44 22.86 21.60 19.75 14.46 15.64 14.54 18.37 8.71 19.34 18.02 23.60 15.59
#> 125 68.1 60 194.1 96.3 20 102 196 143 75 34 28 147
#> 15.65 20.62 13.15 22.40 14.54 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 20.1 160 163 64 152 141 182 109 162 118 72 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 165 147.1 144 28.1 173 151 142.1 182.2 44 12 28.2 28.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 147.2 17 141.1 102.1 152.1 132 182.3 116 109.1 74 47 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 94 122 161 38 7 193 156 137 120 147.3 162.1 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.2 75.1 27 178 173.1 1 196.1 148 1.1 46 19 67 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 27.1 142.2 144.1 102.2 174 47.1 172 54 119 152.2 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[66]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003049815 0.806885043 0.117111217
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.71190941 0.01126019 0.02928152
#> grade_iii, Cure model
#> 1.18506985
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 181 16.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 133 14.65 1 57 0 0
#> 39 15.59 1 37 0 1
#> 130 16.47 1 53 0 1
#> 90 20.94 1 50 0 1
#> 169 22.41 1 46 0 0
#> 29 15.45 1 68 1 0
#> 57 14.46 1 45 0 1
#> 25 6.32 1 34 1 0
#> 110 17.56 1 65 0 1
#> 70 7.38 1 30 1 0
#> 36 21.19 1 48 0 1
#> 68 20.62 1 44 0 0
#> 150 20.33 1 48 0 0
#> 58 19.34 1 39 0 0
#> 69 23.23 1 25 0 1
#> 167 15.55 1 56 1 0
#> 93 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 167.1 15.55 1 56 1 0
#> 32 20.90 1 37 1 0
#> 18 15.21 1 49 1 0
#> 110.1 17.56 1 65 0 1
#> 175 21.91 1 43 0 0
#> 32.1 20.90 1 37 1 0
#> 57.1 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 39.1 15.59 1 37 0 1
#> 51 18.23 1 83 0 1
#> 85 16.44 1 36 0 0
#> 124 9.73 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 189 10.51 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 70.1 7.38 1 30 1 0
#> 37 12.52 1 57 1 0
#> 187 9.92 1 39 1 0
#> 37.1 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 192 16.44 1 31 1 0
#> 133.1 14.65 1 57 0 0
#> 106 16.67 1 49 1 0
#> 42 12.43 1 49 0 1
#> 158 20.14 1 74 1 0
#> 70.2 7.38 1 30 1 0
#> 15 22.68 1 48 0 0
#> 8 18.43 1 32 0 0
#> 180 14.82 1 37 0 0
#> 10 10.53 1 34 0 0
#> 164 23.60 1 76 0 1
#> 114 13.68 1 NA 0 0
#> 49 12.19 1 48 1 0
#> 77 7.27 1 67 0 1
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 167.2 15.55 1 56 1 0
#> 111.1 17.45 1 47 0 1
#> 124.1 9.73 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 106.1 16.67 1 49 1 0
#> 192.1 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 168 23.72 1 70 0 0
#> 51.1 18.23 1 83 0 1
#> 90.1 20.94 1 50 0 1
#> 177 12.53 1 75 0 0
#> 110.2 17.56 1 65 0 1
#> 113 22.86 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 155 13.08 1 26 0 0
#> 18.1 15.21 1 49 1 0
#> 177.1 12.53 1 75 0 0
#> 199 19.81 1 NA 0 1
#> 159 10.55 1 50 0 1
#> 97 19.14 1 65 0 1
#> 77.1 7.27 1 67 0 1
#> 86 23.81 1 58 0 1
#> 77.2 7.27 1 67 0 1
#> 133.2 14.65 1 57 0 0
#> 37.2 12.52 1 57 1 0
#> 86.1 23.81 1 58 0 1
#> 13 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 51.2 18.23 1 83 0 1
#> 15.1 22.68 1 48 0 0
#> 155.1 13.08 1 26 0 0
#> 86.2 23.81 1 58 0 1
#> 52 10.42 1 52 0 1
#> 69.1 23.23 1 25 0 1
#> 184 17.77 1 38 0 0
#> 110.3 17.56 1 65 0 1
#> 69.2 23.23 1 25 0 1
#> 5 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 145 10.07 1 65 1 0
#> 59 10.16 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 59.1 10.16 1 NA 1 0
#> 106.2 16.67 1 49 1 0
#> 52.1 10.42 1 52 0 1
#> 36.1 21.19 1 48 0 1
#> 77.3 7.27 1 67 0 1
#> 149 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 123 13.00 1 44 1 0
#> 51.3 18.23 1 83 0 1
#> 99 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 181.1 16.46 1 45 0 1
#> 133.3 14.65 1 57 0 0
#> 112 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 1.1 24.00 0 23 1 0
#> 73 24.00 0 NA 0 1
#> 137 24.00 0 45 1 0
#> 142 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 47.1 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 104.1 24.00 0 50 1 0
#> 137.1 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 142.1 24.00 0 53 0 0
#> 47.2 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 112.1 24.00 0 61 0 0
#> 95 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 27 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 84 24.00 0 39 0 1
#> 165 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 173 24.00 0 19 0 1
#> 83 24.00 0 6 0 0
#> 104.2 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 62 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 165.1 24.00 0 47 0 0
#> 137.2 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 54 24.00 0 53 1 0
#> 172 24.00 0 41 0 0
#> 54.1 24.00 0 53 1 0
#> 84.1 24.00 0 39 0 1
#> 94 24.00 0 51 0 1
#> 138 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 162.1 24.00 0 51 0 0
#> 62.1 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 3.1 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 62.2 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 176 24.00 0 43 0 1
#> 138.1 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 102.1 24.00 0 49 0 0
#> 161 24.00 0 45 0 0
#> 7.1 24.00 0 37 1 0
#> 44.1 24.00 0 56 0 0
#> 126 24.00 0 48 0 0
#> 165.2 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 198 24.00 0 66 0 1
#> 135 24.00 0 58 1 0
#> 116 24.00 0 58 0 1
#> 182 24.00 0 35 0 0
#> 2.1 24.00 0 9 0 0
#> 65 24.00 0 57 1 0
#> 131.1 24.00 0 66 0 0
#> 87.1 24.00 0 27 0 0
#> 82 24.00 0 34 0 0
#> 38 24.00 0 31 1 0
#> 162.2 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 94.1 24.00 0 51 0 1
#> 22.1 24.00 0 52 1 0
#> 142.2 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.712 NA NA NA
#> 2 age, Cure model 0.0113 NA NA NA
#> 3 grade_ii, Cure model 0.0293 NA NA NA
#> 4 grade_iii, Cure model 1.19 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00305 NA NA NA
#> 2 grade_ii, Survival model 0.807 NA NA NA
#> 3 grade_iii, Survival model 0.117 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71191 0.01126 0.02928 1.18507
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 247.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71190941 0.01126019 0.02928152 1.18506985
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003049815 0.806885043 0.117111217
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.40187626 0.62623571 0.87124731 0.75614357 0.69044911 0.61779711
#> [7] 0.33442563 0.22788290 0.72787077 0.78365557 0.98830968 0.53873219
#> [13] 0.94713863 0.29799071 0.39125485 0.41242774 0.44311933 0.14162183
#> [19] 0.70594514 0.90965029 0.93482128 0.70594514 0.35862619 0.73512465
#> [25] 0.53873219 0.25705546 0.35862619 0.78365557 0.38059188 0.69044911
#> [31] 0.49240115 0.64287028 0.25705546 0.28483190 0.94713863 0.84533924
#> [37] 0.92861654 0.84533924 0.24254597 0.64287028 0.75614357 0.59271690
#> [43] 0.86474477 0.43309640 0.94713863 0.19923256 0.47270966 0.74912051
#> [49] 0.89056001 0.12462373 0.87774012 0.96490772 0.57464269 0.99416093
#> [55] 0.70594514 0.57464269 0.41242774 0.59271690 0.64287028 0.91600474
#> [61] 0.10660535 0.49240115 0.33442563 0.83183360 0.53873219 0.18399699
#> [67] 0.44311933 0.81128640 0.73512465 0.83183360 0.88415725 0.46282731
#> [73] 0.96490772 0.05964173 0.96490772 0.75614357 0.84533924 0.05964173
#> [79] 0.79746365 0.02481039 0.49240115 0.19923256 0.81128640 0.05964173
#> [85] 0.89695774 0.14162183 0.52928163 0.53873219 0.14162183 0.66672731
#> [91] 0.68261140 0.92234798 0.48257088 0.59271690 0.89695774 0.29799071
#> [97] 0.96490772 0.94100974 0.80437827 0.82502462 0.49240115 0.29799071
#> [103] 0.67474610 0.62623571 0.75614357 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 128 181 56 133 39 130 90 169 29 57 25 110 70
#> 20.35 16.46 12.21 14.65 15.59 16.47 20.94 22.41 15.45 14.46 6.32 17.56 7.38
#> 36 68 150 58 69 167 93 16 167.1 32 18 110.1 175
#> 21.19 20.62 20.33 19.34 23.23 15.55 10.33 8.71 15.55 20.90 15.21 17.56 21.91
#> 32.1 57.1 190 39.1 51 85 175.1 153 70.1 37 187 37.1 66
#> 20.90 14.46 20.81 15.59 18.23 16.44 21.91 21.33 7.38 12.52 9.92 12.52 22.13
#> 192 133.1 106 42 158 70.2 15 8 180 10 164 49 77
#> 16.44 14.65 16.67 12.43 20.14 7.38 22.68 18.43 14.82 10.53 23.60 12.19 7.27
#> 111 91 167.2 111.1 150.1 106.1 192.1 61 168 51.1 90.1 177 110.2
#> 17.45 5.33 15.55 17.45 20.33 16.67 16.44 10.12 23.72 18.23 20.94 12.53 17.56
#> 113 58.1 155 18.1 177.1 159 97 77.1 86 77.2 133.2 37.2 86.1
#> 22.86 19.34 13.08 15.21 12.53 10.55 19.14 7.27 23.81 7.27 14.65 12.52 23.81
#> 13 78 51.2 15.1 155.1 86.2 52 69.1 184 110.3 69.2 5 26
#> 14.34 23.88 18.23 22.68 13.08 23.81 10.42 23.23 17.77 17.56 23.23 16.43 15.77
#> 145 88 106.2 52.1 36.1 77.3 149 81 123 51.3 99 79 181.1
#> 10.07 18.37 16.67 10.42 21.19 7.27 8.37 14.06 13.00 18.23 21.19 16.23 16.46
#> 133.3 112 162 104 1 47 185 146 71 1.1 137 142 2
#> 14.65 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 103 104.1 137.1 34 102 142.1 47.2 9 178 112.1 95 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 35 21 28 27 148 84 165 118 22 173 83 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 62 44 165.1 137.2 53 54 172 54.1 84.1 94 138 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 62.1 186 11 3.1 132 131 62.2 98 176 138.1 28.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 7.1 44.1 126 165.2 191 198 135 116 182 2.1 65 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 82 38 162.2 75 94.1 22.1 142.2 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[67]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003626279 0.542371313 0.661278189
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.82728486 0.02138797 -0.43676814
#> grade_iii, Cure model
#> 0.44659299
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 150 20.33 1 48 0 0
#> 129 23.41 1 53 1 0
#> 184 17.77 1 38 0 0
#> 43 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 13 14.34 1 54 0 1
#> 14 12.89 1 21 0 0
#> 124 9.73 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 4 17.64 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 61 10.12 1 36 0 1
#> 133 14.65 1 57 0 0
#> 37 12.52 1 57 1 0
#> 32 20.90 1 37 1 0
#> 157 15.10 1 47 0 0
#> 194 22.40 1 38 0 1
#> 61.1 10.12 1 36 0 1
#> 140 12.68 1 59 1 0
#> 157.1 15.10 1 47 0 0
#> 127 3.53 1 62 0 1
#> 123 13.00 1 44 1 0
#> 78 23.88 1 43 0 0
#> 59.1 10.16 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 136 21.83 1 43 0 1
#> 187 9.92 1 39 1 0
#> 91 5.33 1 61 0 1
#> 192 16.44 1 31 1 0
#> 197 21.60 1 69 1 0
#> 52 10.42 1 52 0 1
#> 153 21.33 1 55 1 0
#> 175 21.91 1 43 0 0
#> 155 13.08 1 26 0 0
#> 101 9.97 1 10 0 1
#> 25 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 166 19.98 1 48 0 0
#> 170 19.54 1 43 0 1
#> 169 22.41 1 46 0 0
#> 89 11.44 1 NA 0 0
#> 55 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 61.2 10.12 1 36 0 1
#> 170.1 19.54 1 43 0 1
#> 183 9.24 1 67 1 0
#> 127.1 3.53 1 62 0 1
#> 61.3 10.12 1 36 0 1
#> 24 23.89 1 38 0 0
#> 13.1 14.34 1 54 0 1
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 13.2 14.34 1 54 0 1
#> 99.1 21.19 1 38 0 1
#> 169.1 22.41 1 46 0 0
#> 26 15.77 1 49 0 1
#> 99.2 21.19 1 38 0 1
#> 43.1 12.10 1 61 0 1
#> 61.4 10.12 1 36 0 1
#> 184.1 17.77 1 38 0 0
#> 10 10.53 1 34 0 0
#> 61.5 10.12 1 36 0 1
#> 139.1 21.49 1 63 1 0
#> 39 15.59 1 37 0 1
#> 100 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 52.1 10.42 1 52 0 1
#> 179.1 18.63 1 42 0 0
#> 45 17.42 1 54 0 1
#> 77.1 7.27 1 67 0 1
#> 69 23.23 1 25 0 1
#> 145.1 10.07 1 65 1 0
#> 159 10.55 1 50 0 1
#> 58 19.34 1 39 0 0
#> 197.1 21.60 1 69 1 0
#> 96 14.54 1 33 0 1
#> 145.2 10.07 1 65 1 0
#> 42 12.43 1 49 0 1
#> 190.1 20.81 1 42 1 0
#> 51 18.23 1 83 0 1
#> 26.1 15.77 1 49 0 1
#> 159.1 10.55 1 50 0 1
#> 167 15.55 1 56 1 0
#> 124.1 9.73 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 78.1 23.88 1 43 0 0
#> 188 16.16 1 46 0 1
#> 177 12.53 1 75 0 0
#> 179.2 18.63 1 42 0 0
#> 81 14.06 1 34 0 0
#> 100.1 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 125 15.65 1 67 1 0
#> 77.2 7.27 1 67 0 1
#> 66 22.13 1 53 0 0
#> 86 23.81 1 58 0 1
#> 90 20.94 1 50 0 1
#> 25.1 6.32 1 34 1 0
#> 49 12.19 1 48 1 0
#> 150.1 20.33 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 14.1 12.89 1 21 0 0
#> 149 8.37 1 33 1 0
#> 125.1 15.65 1 67 1 0
#> 30 17.43 1 78 0 0
#> 25.2 6.32 1 34 1 0
#> 50 10.02 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 6 15.64 1 39 0 0
#> 97 19.14 1 65 0 1
#> 48 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 116 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 2 24.00 0 9 0 0
#> 131 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 84 24.00 0 39 0 1
#> 144 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 75 24.00 0 21 1 0
#> 200 24.00 0 64 0 0
#> 28 24.00 0 67 1 0
#> 102 24.00 0 49 0 0
#> 152 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 172 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 102.1 24.00 0 49 0 0
#> 11 24.00 0 42 0 1
#> 28.1 24.00 0 67 1 0
#> 165 24.00 0 47 0 0
#> 196 24.00 0 19 0 0
#> 53.1 24.00 0 32 0 1
#> 176.1 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 178 24.00 0 52 1 0
#> 62 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 75.1 24.00 0 21 1 0
#> 74 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 2.1 24.00 0 9 0 0
#> 135.1 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 172.1 24.00 0 41 0 0
#> 71.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 3 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 185 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 48.1 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 34 24.00 0 36 0 0
#> 165.1 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 2.2 24.00 0 9 0 0
#> 146 24.00 0 63 1 0
#> 20.1 24.00 0 46 1 0
#> 174.1 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 119 24.00 0 17 0 0
#> 132 24.00 0 55 0 0
#> 173.1 24.00 0 19 0 1
#> 115 24.00 0 NA 1 0
#> 116.1 24.00 0 58 0 1
#> 141 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 53.2 24.00 0 32 0 1
#> 11.2 24.00 0 42 0 1
#> 22 24.00 0 52 1 0
#> 182 24.00 0 35 0 0
#> 7 24.00 0 37 1 0
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 178.1 24.00 0 52 1 0
#> 3.1 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 48.3 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 109.1 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 27 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 120.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.827 NA NA NA
#> 2 age, Cure model 0.0214 NA NA NA
#> 3 grade_ii, Cure model -0.437 NA NA NA
#> 4 grade_iii, Cure model 0.447 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00363 NA NA NA
#> 2 grade_ii, Survival model 0.542 NA NA NA
#> 3 grade_iii, Survival model 0.661 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82728 0.02139 -0.43677 0.44659
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 252.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82728486 0.02138797 -0.43676814 0.44659299
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003626279 0.542371313 0.661278189
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.47975237 0.16079302 0.59580272 0.83861231 0.36139575 0.75347694
#> [7] 0.79324219 0.58746234 0.91472057 0.88111012 0.73955548 0.81942002
#> [13] 0.44031072 0.72559326 0.25504261 0.88111012 0.80637270 0.72559326
#> [19] 0.98981902 0.78664086 0.07640771 0.46998040 0.31953734 0.93685390
#> [25] 0.98463923 0.63662589 0.33466922 0.86920574 0.38600959 0.28815789
#> [31] 0.77998266 0.93132069 0.96906597 0.64453743 0.49895021 0.50860762
#> [37] 0.22010637 0.52687079 0.39808878 0.88111012 0.50860762 0.94235523
#> [43] 0.98981902 0.88111012 0.03197037 0.75347694 0.45057058 0.95325237
#> [49] 0.75347694 0.39808878 0.22010637 0.67514706 0.39808878 0.83861231
#> [55] 0.88111012 0.59580272 0.86312103 0.88111012 0.36139575 0.71143541
#> [61] 0.65998827 0.55337343 0.86920574 0.55337343 0.62862238 0.95325237
#> [67] 0.18231528 0.91472057 0.85098333 0.52687079 0.33466922 0.74655461
#> [73] 0.91472057 0.82587824 0.45057058 0.57899701 0.67514706 0.85098333
#> [79] 0.71855294 0.20132643 0.07640771 0.65232181 0.81290454 0.55337343
#> [85] 0.77331885 0.65998827 0.61229900 0.68987147 0.95325237 0.27170696
#> [91] 0.13563037 0.42981435 0.96906597 0.83227077 0.47975237 0.79324219
#> [97] 0.94781850 0.68987147 0.62047823 0.96906597 0.28815789 0.70423026
#> [103] 0.54462931 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 150 129 184 43 139 13 14 134 145 61 133 37 32
#> 20.33 23.41 17.77 12.10 21.49 14.34 12.89 17.81 10.07 10.12 14.65 12.52 20.90
#> 157 194 61.1 140 157.1 127 123 78 68 136 187 91 192
#> 15.10 22.40 10.12 12.68 15.10 3.53 13.00 23.88 20.62 21.83 9.92 5.33 16.44
#> 197 52 153 175 155 101 25 5 166 170 169 55 99
#> 21.60 10.42 21.33 21.91 13.08 9.97 6.32 16.43 19.98 19.54 22.41 19.34 21.19
#> 61.2 170.1 183 127.1 61.3 24 13.1 190 77 13.2 99.1 169.1 26
#> 10.12 19.54 9.24 3.53 10.12 23.89 14.34 20.81 7.27 14.34 21.19 22.41 15.77
#> 99.2 43.1 61.4 184.1 10 61.5 139.1 39 100 179 52.1 179.1 45
#> 21.19 12.10 10.12 17.77 10.53 10.12 21.49 15.59 16.07 18.63 10.42 18.63 17.42
#> 77.1 69 145.1 159 58 197.1 96 145.2 42 190.1 51 26.1 159.1
#> 7.27 23.23 10.07 10.55 19.34 21.60 14.54 10.07 12.43 20.81 18.23 15.77 10.55
#> 167 113 78.1 188 177 179.2 81 100.1 117 125 77.2 66 86
#> 15.55 22.86 23.88 16.16 12.53 18.63 14.06 16.07 17.46 15.65 7.27 22.13 23.81
#> 90 25.1 49 150.1 14.1 149 125.1 30 25.2 175.1 6 97 48
#> 20.94 6.32 12.19 20.33 12.89 8.37 15.65 17.43 6.32 21.91 15.64 19.14 24.00
#> 151 116 198 2 131 176 20 163 137 71 193 98 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 173 75 200 28 102 152 53 172 186 135 102.1 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 165 196 53.1 176.1 87 178 62 156 75.1 74 64 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 94 172.1 71.1 174 109 72 3 72.1 185 95 48.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 165.1 138 118 2.2 146 20.1 174.1 160 11.1 119 132 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 141 1 53.2 11.2 22 182 7 120 33 178.1 3.1 48.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.3 131.1 147 109.1 12 27 148 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[68]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009928727 0.681051113 0.273716681
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.68153287 0.01518743 -0.13257034
#> grade_iii, Cure model
#> 0.68158368
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 181 16.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 70 7.38 1 30 1 0
#> 76 19.22 1 54 0 1
#> 93 10.33 1 52 0 1
#> 4 17.64 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 13 14.34 1 54 0 1
#> 14 12.89 1 21 0 0
#> 179 18.63 1 42 0 0
#> 26 15.77 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 181.1 16.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 177 12.53 1 75 0 0
#> 69 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 41 18.02 1 40 1 0
#> 158 20.14 1 74 1 0
#> 101 9.97 1 10 0 1
#> 66 22.13 1 53 0 0
#> 88.1 18.37 1 47 0 0
#> 91 5.33 1 61 0 1
#> 99 21.19 1 38 0 1
#> 16 8.71 1 71 0 1
#> 78 23.88 1 43 0 0
#> 149 8.37 1 33 1 0
#> 107 11.18 1 54 1 0
#> 167 15.55 1 56 1 0
#> 154 12.63 1 20 1 0
#> 15 22.68 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 127 3.53 1 62 0 1
#> 66.1 22.13 1 53 0 0
#> 199.1 19.81 1 NA 0 1
#> 39 15.59 1 37 0 1
#> 164 23.60 1 76 0 1
#> 106 16.67 1 49 1 0
#> 99.1 21.19 1 38 0 1
#> 169 22.41 1 46 0 0
#> 149.1 8.37 1 33 1 0
#> 155 13.08 1 26 0 0
#> 77 7.27 1 67 0 1
#> 168.1 23.72 1 70 0 0
#> 6 15.64 1 39 0 0
#> 60 13.15 1 38 1 0
#> 86 23.81 1 58 0 1
#> 139 21.49 1 63 1 0
#> 68 20.62 1 44 0 0
#> 68.1 20.62 1 44 0 0
#> 88.2 18.37 1 47 0 0
#> 55 19.34 1 69 0 1
#> 155.1 13.08 1 26 0 0
#> 190 20.81 1 42 1 0
#> 15.1 22.68 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 189 10.51 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 188 16.16 1 46 0 1
#> 32 20.90 1 37 1 0
#> 8 18.43 1 32 0 0
#> 10 10.53 1 34 0 0
#> 125 15.65 1 67 1 0
#> 111 17.45 1 47 0 1
#> 70.1 7.38 1 30 1 0
#> 58 19.34 1 39 0 0
#> 36 21.19 1 48 0 1
#> 10.1 10.53 1 34 0 0
#> 23.1 16.92 1 61 0 0
#> 194 22.40 1 38 0 1
#> 23.2 16.92 1 61 0 0
#> 170 19.54 1 43 0 1
#> 4.1 17.64 1 NA 0 1
#> 69.1 23.23 1 25 0 1
#> 81 14.06 1 34 0 0
#> 139.1 21.49 1 63 1 0
#> 41.1 18.02 1 40 1 0
#> 184 17.77 1 38 0 0
#> 197 21.60 1 69 1 0
#> 199.2 19.81 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 187 9.92 1 39 1 0
#> 60.1 13.15 1 38 1 0
#> 101.1 9.97 1 10 0 1
#> 154.1 12.63 1 20 1 0
#> 36.1 21.19 1 48 0 1
#> 93.1 10.33 1 52 0 1
#> 5 16.43 1 51 0 1
#> 5.1 16.43 1 51 0 1
#> 195 11.76 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 184.1 17.77 1 38 0 0
#> 145.1 10.07 1 65 1 0
#> 91.1 5.33 1 61 0 1
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 85 16.44 1 36 0 0
#> 114.1 13.68 1 NA 0 0
#> 23.3 16.92 1 61 0 0
#> 170.1 19.54 1 43 0 1
#> 105.1 19.75 1 60 0 0
#> 60.2 13.15 1 38 1 0
#> 113 22.86 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 158.1 20.14 1 74 1 0
#> 96 14.54 1 33 0 1
#> 99.2 21.19 1 38 0 1
#> 26.1 15.77 1 49 0 1
#> 63 22.77 1 31 1 0
#> 197.1 21.60 1 69 1 0
#> 178 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 2 24.00 0 9 0 0
#> 75 24.00 0 21 1 0
#> 131 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 109 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 22 24.00 0 52 1 0
#> 151 24.00 0 42 0 0
#> 191 24.00 0 60 0 1
#> 196 24.00 0 19 0 0
#> 7 24.00 0 37 1 0
#> 87 24.00 0 27 0 0
#> 147 24.00 0 76 1 0
#> 118 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 165 24.00 0 47 0 0
#> 173 24.00 0 19 0 1
#> 185 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 151.1 24.00 0 42 0 0
#> 200 24.00 0 64 0 0
#> 112 24.00 0 61 0 0
#> 191.1 24.00 0 60 0 1
#> 144.1 24.00 0 28 0 1
#> 34 24.00 0 36 0 0
#> 160 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 200.1 24.00 0 64 0 0
#> 112.1 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 126 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 200.2 24.00 0 64 0 0
#> 115 24.00 0 NA 1 0
#> 98 24.00 0 34 1 0
#> 152 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 71 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 109.1 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 131.1 24.00 0 66 0 0
#> 64.1 24.00 0 43 0 0
#> 173.1 24.00 0 19 0 1
#> 109.2 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 141 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 156 24.00 0 50 1 0
#> 173.2 24.00 0 19 0 1
#> 151.2 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 146.1 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 1 24.00 0 23 1 0
#> 185.1 24.00 0 44 1 0
#> 54.1 24.00 0 53 1 0
#> 160.1 24.00 0 31 1 0
#> 67.1 24.00 0 25 0 0
#> 34.1 24.00 0 36 0 0
#> 138.1 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 48.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 53.1 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 151.3 24.00 0 42 0 0
#> 147.1 24.00 0 76 1 0
#> 118.1 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.682 NA NA NA
#> 2 age, Cure model 0.0152 NA NA NA
#> 3 grade_ii, Cure model -0.133 NA NA NA
#> 4 grade_iii, Cure model 0.682 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00993 NA NA NA
#> 2 grade_ii, Survival model 0.681 NA NA NA
#> 3 grade_iii, Survival model 0.274 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.68153 0.01519 -0.13257 0.68158
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 250.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.68153287 0.01518743 -0.13257034 0.68158368
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009928727 0.681051113 0.273716681
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4976615539 0.9336027781 0.3216634744 0.8105783494 0.4442666198
#> [6] 0.6428418579 0.7326010821 0.3316045726 0.5638063265 0.4976615539
#> [11] 0.2367916718 0.8330362680 0.7659259899 0.0337216921 0.3618113777
#> [16] 0.3925585423 0.2460656016 0.8554722513 0.1047690213 0.3618113777
#> [21] 0.9666345972 0.1583062772 0.8889819200 0.0039295224 0.9114080820
#> [26] 0.7771023421 0.6201514678 0.7439038718 0.0715368224 0.0134252553
#> [31] 0.9888119205 0.1047690213 0.6087839462 0.0257238852 0.4867320065
#> [36] 0.1583062772 0.0874141756 0.9114080820 0.6988706918 0.9555538309
#> [41] 0.0134252553 0.5974353735 0.6656930329 0.0082960388 0.1405394547
#> [46] 0.2186566207 0.2186566207 0.3618113777 0.3022250373 0.6988706918
#> [51] 0.2096629795 0.0715368224 0.3316045726 0.8889819200 0.5526047261
#> [56] 0.2005513076 0.3515914758 0.7882536906 0.5861555967 0.4337230129
#> [61] 0.9336027781 0.3022250373 0.1583062772 0.7882536906 0.4442666198
#> [66] 0.0960527927 0.4442666198 0.2831898644 0.0337216921 0.6542388600
#> [71] 0.1405394547 0.3925585423 0.4129795207 0.1226466720 0.7213310193
#> [76] 0.8777966994 0.6656930329 0.8554722513 0.7439038718 0.1583062772
#> [81] 0.8105783494 0.5305027582 0.5305027582 0.2643351358 0.4129795207
#> [86] 0.8330362680 0.9666345972 0.0009141033 0.0477624890 0.5194310378
#> [91] 0.4442666198 0.2831898644 0.2643351358 0.6656930329 0.0556146703
#> [96] 0.2460656016 0.6314913096 0.1583062772 0.5638063265 0.0637993655
#> [101] 0.1226466720 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 181 70 76 93 23 13 14 179 26 181.1 128 145 177
#> 16.46 7.38 19.22 10.33 16.92 14.34 12.89 18.63 15.77 16.46 20.35 10.07 12.53
#> 69 88 41 158 101 66 88.1 91 99 16 78 149 107
#> 23.23 18.37 18.02 20.14 9.97 22.13 18.37 5.33 21.19 8.71 23.88 8.37 11.18
#> 167 154 15 168 127 66.1 39 164 106 99.1 169 149.1 155
#> 15.55 12.63 22.68 23.72 3.53 22.13 15.59 23.60 16.67 21.19 22.41 8.37 13.08
#> 77 168.1 6 60 86 139 68 68.1 88.2 55 155.1 190 15.1
#> 7.27 23.72 15.64 13.15 23.81 21.49 20.62 20.62 18.37 19.34 13.08 20.81 22.68
#> 179.1 16.1 188 32 8 10 125 111 70.1 58 36 10.1 23.1
#> 18.63 8.71 16.16 20.90 18.43 10.53 15.65 17.45 7.38 19.34 21.19 10.53 16.92
#> 194 23.2 170 69.1 81 139.1 41.1 184 197 123 187 60.1 101.1
#> 22.40 16.92 19.54 23.23 14.06 21.49 18.02 17.77 21.60 13.00 9.92 13.15 9.97
#> 154.1 36.1 93.1 5 5.1 105 184.1 145.1 91.1 24 92 85 23.3
#> 12.63 21.19 10.33 16.43 16.43 19.75 17.77 10.07 5.33 23.89 22.92 16.44 16.92
#> 170.1 105.1 60.2 113 158.1 96 99.2 26.1 63 197.1 178 119 2
#> 19.54 19.75 13.15 22.86 20.14 14.54 21.19 15.77 22.77 21.60 24.00 24.00 24.00
#> 75 131 178.1 64 109 83 22 151 191 196 7 87 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 144 165 173 185 176 21 146 151.1 200 112 191.1 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 160 182 193 143 176.1 138 200.1 112.1 17 126 172 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 200.2 98 152 9 71 104 109.1 19 135 131.1 64.1 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.2 126.1 95 53 141 48 174 54 156 173.2 151.2 31 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 1 185.1 54.1 160.1 67.1 34.1 138.1 163 103 48.1 82 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 151.3 147.1 118.1 72
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[69]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008153971 0.665857591 0.569260149
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.1830776246 0.0006661639 0.4291228181
#> grade_iii, Cure model
#> 0.9110720489
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 85 16.44 1 36 0 0
#> 51 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 15 22.68 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 6 15.64 1 39 0 0
#> 139.1 21.49 1 63 1 0
#> 167 15.55 1 56 1 0
#> 180 14.82 1 37 0 0
#> 177 12.53 1 75 0 0
#> 37 12.52 1 57 1 0
#> 101 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 136 21.83 1 43 0 1
#> 13 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 49 12.19 1 48 1 0
#> 129 23.41 1 53 1 0
#> 90 20.94 1 50 0 1
#> 168 23.72 1 70 0 0
#> 30 17.43 1 78 0 0
#> 134 17.81 1 47 1 0
#> 190 20.81 1 42 1 0
#> 169 22.41 1 46 0 0
#> 97 19.14 1 65 0 1
#> 187 9.92 1 39 1 0
#> 69.1 23.23 1 25 0 1
#> 157 15.10 1 47 0 0
#> 77 7.27 1 67 0 1
#> 10 10.53 1 34 0 0
#> 43 12.10 1 61 0 1
#> 127 3.53 1 62 0 1
#> 150 20.33 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 68 20.62 1 44 0 0
#> 101.1 9.97 1 10 0 1
#> 69.2 23.23 1 25 0 1
#> 96 14.54 1 33 0 1
#> 10.2 10.53 1 34 0 0
#> 42 12.43 1 49 0 1
#> 15.1 22.68 1 48 0 0
#> 133 14.65 1 57 0 0
#> 166 19.98 1 48 0 0
#> 123 13.00 1 44 1 0
#> 66 22.13 1 53 0 0
#> 59 10.16 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 170 19.54 1 43 0 1
#> 199.1 19.81 1 NA 0 1
#> 114.1 13.68 1 NA 0 0
#> 175 21.91 1 43 0 0
#> 61 10.12 1 36 0 1
#> 57 14.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 4.1 17.64 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 192 16.44 1 31 1 0
#> 117 17.46 1 26 0 1
#> 25 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 45 17.42 1 54 0 1
#> 177.1 12.53 1 75 0 0
#> 59.1 10.16 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 16 8.71 1 71 0 1
#> 170.1 19.54 1 43 0 1
#> 13.1 14.34 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 63 22.77 1 31 1 0
#> 15.2 22.68 1 48 0 0
#> 199.2 19.81 1 NA 0 1
#> 123.1 13.00 1 44 1 0
#> 8 18.43 1 32 0 0
#> 36 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 30.1 17.43 1 78 0 0
#> 184 17.77 1 38 0 0
#> 32 20.90 1 37 1 0
#> 111 17.45 1 47 0 1
#> 107 11.18 1 54 1 0
#> 168.1 23.72 1 70 0 0
#> 4.2 17.64 1 NA 0 1
#> 88.1 18.37 1 47 0 0
#> 167.1 15.55 1 56 1 0
#> 79 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 57.1 14.46 1 45 0 1
#> 184.1 17.77 1 38 0 0
#> 66.1 22.13 1 53 0 0
#> 81 14.06 1 34 0 0
#> 59.2 10.16 1 NA 1 0
#> 123.2 13.00 1 44 1 0
#> 26 15.77 1 49 0 1
#> 140.1 12.68 1 59 1 0
#> 79.1 16.23 1 54 1 0
#> 114.2 13.68 1 NA 0 0
#> 184.2 17.77 1 38 0 0
#> 189 10.51 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 113.1 22.86 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 150.1 20.33 1 48 0 0
#> 136.1 21.83 1 43 0 1
#> 93 10.33 1 52 0 1
#> 18 15.21 1 49 1 0
#> 99 21.19 1 38 0 1
#> 32.1 20.90 1 37 1 0
#> 75 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 33 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 9 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 83 24.00 0 6 0 0
#> 186 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 161 24.00 0 45 0 0
#> 115 24.00 0 NA 1 0
#> 200 24.00 0 64 0 0
#> 148.1 24.00 0 61 1 0
#> 132.1 24.00 0 55 0 0
#> 119 24.00 0 17 0 0
#> 64 24.00 0 43 0 0
#> 115.1 24.00 0 NA 1 0
#> 200.1 24.00 0 64 0 0
#> 64.1 24.00 0 43 0 0
#> 120 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 122.1 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 31 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 122.2 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 34.1 24.00 0 36 0 0
#> 20 24.00 0 46 1 0
#> 144 24.00 0 28 0 1
#> 126 24.00 0 48 0 0
#> 38.1 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 20.1 24.00 0 46 1 0
#> 65 24.00 0 57 1 0
#> 64.2 24.00 0 43 0 0
#> 73.1 24.00 0 NA 0 1
#> 151.1 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 73.2 24.00 0 NA 0 1
#> 72 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 122.3 24.00 0 66 0 0
#> 72.1 24.00 0 40 0 1
#> 115.2 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 73.3 24.00 0 NA 0 1
#> 142 24.00 0 53 0 0
#> 12.1 24.00 0 63 0 0
#> 200.2 24.00 0 64 0 0
#> 73.4 24.00 0 NA 0 1
#> 74 24.00 0 43 0 1
#> 142.1 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 27 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 200.3 24.00 0 64 0 0
#> 122.4 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 118 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 102.1 24.00 0 49 0 0
#> 84.1 24.00 0 39 0 1
#> 176 24.00 0 43 0 1
#> 38.2 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 200.4 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 162.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.183 NA NA NA
#> 2 age, Cure model 0.000666 NA NA NA
#> 3 grade_ii, Cure model 0.429 NA NA NA
#> 4 grade_iii, Cure model 0.911 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00815 NA NA NA
#> 2 grade_ii, Survival model 0.666 NA NA NA
#> 3 grade_iii, Survival model 0.569 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1830776 0.0006662 0.4291228 0.9110720
#>
#> Degrees of Freedom: 177 Total (i.e. Null); 174 Residual
#> Null Deviance: 244.9
#> Residual Deviance: 239.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1830776246 0.0006661639 0.4291228181 0.9110720489
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008153971 0.665857591 0.569260149
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.63644850 0.74937472 0.65294610 0.22845119 0.33301703 0.47397974
#> [7] 0.79519741 0.47397974 0.80145006 0.82544141 0.90840076 0.91862797
#> [13] 0.96753348 0.87133420 0.44864718 0.85457549 0.92872006 0.20129106
#> [19] 0.51774617 0.13386041 0.72117266 0.67663271 0.54733121 0.37739290
#> [25] 0.61960409 0.97697075 0.22845119 0.81948977 0.98630705 0.94348739
#> [31] 0.93369304 0.99547347 0.57516613 0.94348739 0.55675151 0.96753348
#> [37] 0.22845119 0.83728956 0.94348739 0.92369655 0.33301703 0.83137797
#> [43] 0.59330267 0.87686614 0.40652988 0.28136506 0.60237439 0.43458129
#> [49] 0.96276048 0.84314686 0.66887954 0.74245126 0.78892629 0.74937472
#> [55] 0.70648212 0.99090688 0.76292747 0.73541481 0.90840076 0.90322338
#> [61] 0.98166279 0.60237439 0.85457549 0.06427953 0.31640710 0.33301703
#> [67] 0.87686614 0.62804313 0.49659054 0.66099427 0.72117266 0.68422452
#> [73] 0.52808095 0.71388755 0.93861605 0.13386041 0.63644850 0.80145006
#> [79] 0.76963381 0.89282156 0.84314686 0.68422452 0.40652988 0.86574359
#> [85] 0.87686614 0.78253525 0.89282156 0.76963381 0.68422452 0.37739290
#> [91] 0.28136506 0.55675151 0.57516613 0.44864718 0.95795484 0.81351788
#> [97] 0.49659054 0.52808095 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 88 85 51 69 15 139 6 139.1 167 180 177 37 101
#> 18.37 16.44 18.23 23.23 22.68 21.49 15.64 21.49 15.55 14.82 12.53 12.52 9.97
#> 60 136 13 49 129 90 168 30 134 190 169 97 187
#> 13.15 21.83 14.34 12.19 23.41 20.94 23.72 17.43 17.81 20.81 22.41 19.14 9.92
#> 69.1 157 77 10 43 127 150 10.1 68 101.1 69.2 96 10.2
#> 23.23 15.10 7.27 10.53 12.10 3.53 20.33 10.53 20.62 9.97 23.23 14.54 10.53
#> 42 15.1 133 166 123 66 113 170 175 61 57 40 130
#> 12.43 22.68 14.65 19.98 13.00 22.13 22.86 19.54 21.91 10.12 14.46 18.00 16.47
#> 125 192 117 25 5 45 177.1 154 16 170.1 13.1 24 63
#> 15.65 16.44 17.46 6.32 16.43 17.42 12.53 12.63 8.71 19.54 14.34 23.89 22.77
#> 15.2 123.1 8 36 41 30.1 184 32 111 107 168.1 88.1 167.1
#> 22.68 13.00 18.43 21.19 18.02 17.43 17.77 20.90 17.45 11.18 23.72 18.37 15.55
#> 79 140 57.1 184.1 66.1 81 123.2 26 140.1 79.1 184.2 169.1 113.1
#> 16.23 12.68 14.46 17.77 22.13 14.06 13.00 15.77 12.68 16.23 17.77 22.41 22.86
#> 68.1 150.1 136.1 93 18 99 32.1 75 33 141 148 9 151
#> 20.62 20.33 21.83 10.33 15.21 21.19 20.90 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 186 35 122 46 132 161 200 148.1 132.1 119 64 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 120 34 122.1 62 38 3 143 83.1 31 141.1 174 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 122.2 121 48 94 34.1 20 144 126 38.1 12 20.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.2 151.1 162 72 53 122.3 72.1 193 142 12.1 200.2 74 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 160 22 84 27 165 200.3 122.4 102 109 152 118 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 84.1 176 38.2 35.1 200.4 163 162.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[70]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007560695 0.315430145 0.038952233
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.74422858 0.01532052 0.03829101
#> grade_iii, Cure model
#> 0.59295349
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 57 14.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 69 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 97 19.14 1 65 0 1
#> 130.1 16.47 1 53 0 1
#> 85 16.44 1 36 0 0
#> 86 23.81 1 58 0 1
#> 105 19.75 1 60 0 0
#> 91 5.33 1 61 0 1
#> 6 15.64 1 39 0 0
#> 5 16.43 1 51 0 1
#> 105.1 19.75 1 60 0 0
#> 170 19.54 1 43 0 1
#> 155 13.08 1 26 0 0
#> 57.1 14.46 1 45 0 1
#> 52 10.42 1 52 0 1
#> 86.1 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 30 17.43 1 78 0 0
#> 91.1 5.33 1 61 0 1
#> 26 15.77 1 49 0 1
#> 154 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 68 20.62 1 44 0 0
#> 26.1 15.77 1 49 0 1
#> 125 15.65 1 67 1 0
#> 13 14.34 1 54 0 1
#> 158 20.14 1 74 1 0
#> 96 14.54 1 33 0 1
#> 15 22.68 1 48 0 0
#> 5.1 16.43 1 51 0 1
#> 155.1 13.08 1 26 0 0
#> 155.2 13.08 1 26 0 0
#> 58 19.34 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 23.1 16.92 1 61 0 0
#> 133 14.65 1 57 0 0
#> 36 21.19 1 48 0 1
#> 59 10.16 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 40 18.00 1 28 1 0
#> 97.1 19.14 1 65 0 1
#> 57.2 14.46 1 45 0 1
#> 90.1 20.94 1 50 0 1
#> 41 18.02 1 40 1 0
#> 158.1 20.14 1 74 1 0
#> 149 8.37 1 33 1 0
#> 154.1 12.63 1 20 1 0
#> 56 12.21 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 168 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 179 18.63 1 42 0 0
#> 170.1 19.54 1 43 0 1
#> 150.2 20.33 1 48 0 0
#> 188 16.16 1 46 0 1
#> 127 3.53 1 62 0 1
#> 77 7.27 1 67 0 1
#> 128 20.35 1 35 0 1
#> 18 15.21 1 49 1 0
#> 36.1 21.19 1 48 0 1
#> 66 22.13 1 53 0 0
#> 125.1 15.65 1 67 1 0
#> 180 14.82 1 37 0 0
#> 110 17.56 1 65 0 1
#> 187 9.92 1 39 1 0
#> 93 10.33 1 52 0 1
#> 101 9.97 1 10 0 1
#> 86.2 23.81 1 58 0 1
#> 117 17.46 1 26 0 1
#> 43 12.10 1 61 0 1
#> 158.2 20.14 1 74 1 0
#> 25 6.32 1 34 1 0
#> 117.1 17.46 1 26 0 1
#> 61 10.12 1 36 0 1
#> 197 21.60 1 69 1 0
#> 123 13.00 1 44 1 0
#> 63 22.77 1 31 1 0
#> 49 12.19 1 48 1 0
#> 90.2 20.94 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 60 13.15 1 38 1 0
#> 18.1 15.21 1 49 1 0
#> 86.3 23.81 1 58 0 1
#> 81 14.06 1 34 0 0
#> 13.1 14.34 1 54 0 1
#> 61.1 10.12 1 36 0 1
#> 25.1 6.32 1 34 1 0
#> 6.1 15.64 1 39 0 0
#> 195.1 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 30.1 17.43 1 78 0 0
#> 5.2 16.43 1 51 0 1
#> 37 12.52 1 57 1 0
#> 32 20.90 1 37 1 0
#> 117.2 17.46 1 26 0 1
#> 49.1 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 90.3 20.94 1 50 0 1
#> 88 18.37 1 47 0 0
#> 63.1 22.77 1 31 1 0
#> 167 15.55 1 56 1 0
#> 190 20.81 1 42 1 0
#> 24 23.89 1 38 0 0
#> 82 24.00 0 34 0 0
#> 94 24.00 0 51 0 1
#> 193 24.00 0 45 0 1
#> 109 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 152 24.00 0 36 0 1
#> 112 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 152.1 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 7 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 176 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 7.1 24.00 0 37 1 0
#> 200 24.00 0 64 0 0
#> 121 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 7.2 24.00 0 37 1 0
#> 151.1 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 7.3 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 94.1 24.00 0 51 0 1
#> 73.1 24.00 0 NA 0 1
#> 148 24.00 0 61 1 0
#> 74 24.00 0 43 0 1
#> 121.1 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 98.1 24.00 0 34 1 0
#> 2 24.00 0 9 0 0
#> 2.1 24.00 0 9 0 0
#> 64 24.00 0 43 0 0
#> 28 24.00 0 67 1 0
#> 27 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 151.2 24.00 0 42 0 0
#> 98.2 24.00 0 34 1 0
#> 11.1 24.00 0 42 0 1
#> 22 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 147.1 24.00 0 76 1 0
#> 94.2 24.00 0 51 0 1
#> 112.1 24.00 0 61 0 0
#> 7.4 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 94.3 24.00 0 51 0 1
#> 173.1 24.00 0 19 0 1
#> 144.1 24.00 0 28 0 1
#> 151.3 24.00 0 42 0 0
#> 165.1 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 147.2 24.00 0 76 1 0
#> 152.2 24.00 0 36 0 1
#> 44.1 24.00 0 56 0 0
#> 161 24.00 0 45 0 0
#> 20.1 24.00 0 46 1 0
#> 109.1 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 27.1 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 94.4 24.00 0 51 0 1
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 84 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 173.2 24.00 0 19 0 1
#> 152.3 24.00 0 36 0 1
#> 200.1 24.00 0 64 0 0
#> 141 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 104.1 24.00 0 50 1 0
#> 44.2 24.00 0 56 0 0
#> 109.2 24.00 0 48 0 0
#> 161.1 24.00 0 45 0 0
#> 31 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 162 24.00 0 51 0 0
#> 27.2 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.744 NA NA NA
#> 2 age, Cure model 0.0153 NA NA NA
#> 3 grade_ii, Cure model 0.0383 NA NA NA
#> 4 grade_iii, Cure model 0.593 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00756 NA NA NA
#> 2 grade_ii, Survival model 0.315 NA NA NA
#> 3 grade_iii, Survival model 0.0390 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74423 0.01532 0.03829 0.59295
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 257.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74422858 0.01532052 0.03829101 0.59295349
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007560695 0.315430145 0.038952233
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.595443204 0.374753947 0.028031111 0.143860491 0.143860491 0.234088435
#> [7] 0.374753947 0.394761876 0.006816946 0.191115764 0.964076015 0.508535413
#> [13] 0.414848327 0.191115764 0.207991932 0.673645942 0.595443204 0.833968688
#> [19] 0.006816946 0.394761876 0.335772048 0.964076015 0.466214434 0.718929066
#> [25] 0.065235301 0.128340019 0.466214434 0.487294931 0.628458940 0.167124322
#> [31] 0.584390660 0.045684929 0.414848327 0.673645942 0.673645942 0.225216484
#> [37] 0.085684819 0.355065276 0.355065276 0.573377667 0.072037714 0.455688195
#> [43] 0.289185128 0.234088435 0.595443204 0.085684819 0.279821500 0.167124322
#> [49] 0.916616393 0.718929066 0.764501578 0.810643276 0.021860211 0.822282197
#> [55] 0.251980753 0.207991932 0.143860491 0.445249898 0.987942572 0.928485355
#> [61] 0.136055499 0.540873522 0.072037714 0.051979642 0.487294931 0.562438243
#> [67] 0.298515763 0.892884586 0.845704233 0.881028954 0.006816946 0.307953782
#> [73] 0.799019157 0.167124322 0.940411259 0.307953782 0.857488554 0.058537220
#> [79] 0.707467464 0.034402577 0.776054258 0.085684819 0.261182165 0.662281679
#> [85] 0.540873522 0.006816946 0.650911855 0.628458940 0.857488554 0.940411259
#> [91] 0.508535413 0.741541956 0.335772048 0.414848327 0.753012218 0.113168547
#> [97] 0.307953782 0.776054258 0.904736951 0.085684819 0.270453799 0.034402577
#> [103] 0.530004992 0.120753700 0.001797827 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 57 130 69 150 150.1 97 130.1 85 86 105 91 6 5
#> 14.46 16.47 23.23 20.33 20.33 19.14 16.47 16.44 23.81 19.75 5.33 15.64 16.43
#> 105.1 170 155 57.1 52 86.1 192 30 91.1 26 154 139 68
#> 19.75 19.54 13.08 14.46 10.42 23.81 16.44 17.43 5.33 15.77 12.63 21.49 20.62
#> 26.1 125 13 158 96 15 5.1 155.1 155.2 58 90 23 23.1
#> 15.77 15.65 14.34 20.14 14.54 22.68 16.43 13.08 13.08 19.34 20.94 16.92 16.92
#> 133 36 100 40 97.1 57.2 90.1 41 158.1 149 154.1 56 107
#> 14.65 21.19 16.07 18.00 19.14 14.46 20.94 18.02 20.14 8.37 12.63 12.21 11.18
#> 168 159 179 170.1 150.2 188 127 77 128 18 36.1 66 125.1
#> 23.72 10.55 18.63 19.54 20.33 16.16 3.53 7.27 20.35 15.21 21.19 22.13 15.65
#> 180 110 187 93 101 86.2 117 43 158.2 25 117.1 61 197
#> 14.82 17.56 9.92 10.33 9.97 23.81 17.46 12.10 20.14 6.32 17.46 10.12 21.60
#> 123 63 49 90.2 8 60 18.1 86.3 81 13.1 61.1 25.1 6.1
#> 13.00 22.77 12.19 20.94 18.43 13.15 15.21 23.81 14.06 14.34 10.12 6.32 15.64
#> 177 30.1 5.2 37 32 117.2 49.1 183 90.3 88 63.1 167 190
#> 12.53 17.43 16.43 12.52 20.90 17.46 12.19 9.24 20.94 18.37 22.77 15.55 20.81
#> 24 82 94 193 109 165 80 151 152 112 20 152.1 104
#> 23.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 7 176 146 7.1 200 121 98 116 7.2 151.1 198 7.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 94.1 148 74 121.1 44 98.1 2 2.1 64 28 27 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.2 98.2 11.1 22 160 173 147.1 94.2 112.1 7.4 144 94.3 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 151.3 165.1 163 48 147.2 152.2 44.1 161 20.1 109.1 185 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 34 94.4 83 119 84 67 173.2 152.3 200.1 141 132 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.2 109.2 161.1 31 38 191 162 27.2 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[71]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003943823 1.155406643 0.680441569
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.700997028 0.007742821 0.429910116
#> grade_iii, Cure model
#> 1.188108789
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 55 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 114 13.68 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 149 8.37 1 33 1 0
#> 57 14.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 15 22.68 1 48 0 0
#> 91 5.33 1 61 0 1
#> 66 22.13 1 53 0 0
#> 76 19.22 1 54 0 1
#> 145 10.07 1 65 1 0
#> 128 20.35 1 35 0 1
#> 42 12.43 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 199.1 19.81 1 NA 0 1
#> 58 19.34 1 39 0 0
#> 113 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 199.2 19.81 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 92 22.92 1 47 0 1
#> 153 21.33 1 55 1 0
#> 24 23.89 1 38 0 0
#> 183.1 9.24 1 67 1 0
#> 41 18.02 1 40 1 0
#> 128.1 20.35 1 35 0 1
#> 123 13.00 1 44 1 0
#> 195 11.76 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 123.1 13.00 1 44 1 0
#> 55.1 19.34 1 69 0 1
#> 4 17.64 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 39 15.59 1 37 0 1
#> 30 17.43 1 78 0 0
#> 78 23.88 1 43 0 0
#> 26 15.77 1 49 0 1
#> 63 22.77 1 31 1 0
#> 187.1 9.92 1 39 1 0
#> 99 21.19 1 38 0 1
#> 32 20.90 1 37 1 0
#> 52 10.42 1 52 0 1
#> 167 15.55 1 56 1 0
#> 117 17.46 1 26 0 1
#> 15.1 22.68 1 48 0 0
#> 70 7.38 1 30 1 0
#> 15.2 22.68 1 48 0 0
#> 108 18.29 1 39 0 1
#> 166 19.98 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 79 16.23 1 54 1 0
#> 110 17.56 1 65 0 1
#> 70.1 7.38 1 30 1 0
#> 183.2 9.24 1 67 1 0
#> 123.2 13.00 1 44 1 0
#> 114.1 13.68 1 NA 0 0
#> 194 22.40 1 38 0 1
#> 114.2 13.68 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 184 17.77 1 38 0 0
#> 183.3 9.24 1 67 1 0
#> 111 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 149.1 8.37 1 33 1 0
#> 29 15.45 1 68 1 0
#> 184.1 17.77 1 38 0 0
#> 14 12.89 1 21 0 0
#> 91.1 5.33 1 61 0 1
#> 134 17.81 1 47 1 0
#> 96 14.54 1 33 0 1
#> 24.1 23.89 1 38 0 0
#> 167.1 15.55 1 56 1 0
#> 159 10.55 1 50 0 1
#> 91.2 5.33 1 61 0 1
#> 26.1 15.77 1 49 0 1
#> 58.1 19.34 1 39 0 0
#> 150.1 20.33 1 48 0 0
#> 6 15.64 1 39 0 0
#> 159.1 10.55 1 50 0 1
#> 129 23.41 1 53 1 0
#> 55.2 19.34 1 69 0 1
#> 134.1 17.81 1 47 1 0
#> 78.1 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 181 16.46 1 45 0 1
#> 91.3 5.33 1 61 0 1
#> 108.1 18.29 1 39 0 1
#> 90 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 92.1 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 136.1 21.83 1 43 0 1
#> 70.2 7.38 1 30 1 0
#> 179 18.63 1 42 0 0
#> 97 19.14 1 65 0 1
#> 108.2 18.29 1 39 0 1
#> 49 12.19 1 48 1 0
#> 26.2 15.77 1 49 0 1
#> 60 13.15 1 38 1 0
#> 123.3 13.00 1 44 1 0
#> 189 10.51 1 NA 1 0
#> 199.3 19.81 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 184.2 17.77 1 38 0 0
#> 157 15.10 1 47 0 0
#> 197 21.60 1 69 1 0
#> 170.1 19.54 1 43 0 1
#> 71 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 73 24.00 0 NA 0 1
#> 98 24.00 0 34 1 0
#> 20 24.00 0 46 1 0
#> 65 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 80 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 151 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 27 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 80.1 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 119 24.00 0 17 0 0
#> 80.2 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 64.1 24.00 0 43 0 0
#> 182 24.00 0 35 0 0
#> 162 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 152 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 178 24.00 0 52 1 0
#> 185.1 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 19.1 24.00 0 57 0 1
#> 22 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 38.1 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 182.1 24.00 0 35 0 0
#> 38.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 80.3 24.00 0 41 0 0
#> 27.1 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 161.1 24.00 0 45 0 0
#> 44 24.00 0 56 0 0
#> 72 24.00 0 40 0 1
#> 2.1 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 135.1 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 82.1 24.00 0 34 0 0
#> 132 24.00 0 55 0 0
#> 19.2 24.00 0 57 0 1
#> 122.1 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 103.1 24.00 0 56 1 0
#> 196 24.00 0 19 0 0
#> 144 24.00 0 28 0 1
#> 21.1 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 161.2 24.00 0 45 0 0
#> 11 24.00 0 42 0 1
#> 161.3 24.00 0 45 0 0
#> 186.1 24.00 0 45 1 0
#> 151.1 24.00 0 42 0 0
#> 80.4 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 151.2 24.00 0 42 0 0
#> 19.3 24.00 0 57 0 1
#> 11.1 24.00 0 42 0 1
#> 141 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 65.2 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 64.2 24.00 0 43 0 0
#> 156.1 24.00 0 50 1 0
#> 19.4 24.00 0 57 0 1
#> 165 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.701 NA NA NA
#> 2 age, Cure model 0.00774 NA NA NA
#> 3 grade_ii, Cure model 0.430 NA NA NA
#> 4 grade_iii, Cure model 1.19 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00394 NA NA NA
#> 2 grade_ii, Survival model 1.16 NA NA NA
#> 3 grade_iii, Survival model 0.680 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.700997 0.007743 0.429910 1.188109
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 249.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.700997028 0.007742821 0.429910116 1.188108789
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003943823 1.155406643 0.680441569
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.89258225 0.54534074 0.83483005 0.59135616 0.93508311 0.93051761
#> [7] 0.96064547 0.84601068 0.99614329 0.35874048 0.98071546 0.41902490
#> [13] 0.63198855 0.92592836 0.52648158 0.89749210 0.43386081 0.59135616
#> [19] 0.32399495 0.88760573 0.94395813 0.28774856 0.47303574 0.05599992
#> [25] 0.94395813 0.68684006 0.52648158 0.86246003 0.65621563 0.86246003
#> [31] 0.59135616 0.82358333 0.80001500 0.74910317 0.13244588 0.77535749
#> [37] 0.34250289 0.93508311 0.48456325 0.51650933 0.92126744 0.80614857
#> [43] 0.73564159 0.35874048 0.96883867 0.35874048 0.66420643 0.56406502
#> [49] 0.89749210 0.76893864 0.72879389 0.96883867 0.94395813 0.86246003
#> [55] 0.40406594 0.76235891 0.70814500 0.94395813 0.74241439 0.85152845
#> [61] 0.96064547 0.81784425 0.70814500 0.88254385 0.98071546 0.69424547
#> [67] 0.84044359 0.05599992 0.80614857 0.91190184 0.98071546 0.77535749
#> [73] 0.59135616 0.54534074 0.79382040 0.91190184 0.23953667 0.59135616
#> [79] 0.69424547 0.13244588 0.57347336 0.75577052 0.98071546 0.66420643
#> [85] 0.50599420 0.48456325 0.28774856 0.26493069 0.43386081 0.96883867
#> [91] 0.64820497 0.64017643 0.66420643 0.90713804 0.77535749 0.85704110
#> [97] 0.86246003 0.20282480 0.70814500 0.82921058 0.46061720 0.57347336
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 154 150 180 55 187 101 149 57 127 15 91 66 76
#> 12.63 20.33 14.82 19.34 9.92 9.97 8.37 14.46 3.53 22.68 5.33 22.13 19.22
#> 145 128 42 136 58 113 140 183 92 153 24 183.1 41
#> 10.07 20.35 12.43 21.83 19.34 22.86 12.68 9.24 22.92 21.33 23.89 9.24 18.02
#> 128.1 123 88 123.1 55.1 18 39 30 78 26 63 187.1 99
#> 20.35 13.00 18.37 13.00 19.34 15.21 15.59 17.43 23.88 15.77 22.77 9.92 21.19
#> 32 52 167 117 15.1 70 15.2 108 166 42.1 79 110 70.1
#> 20.90 10.42 15.55 17.46 22.68 7.38 22.68 18.29 19.98 12.43 16.23 17.56 7.38
#> 183.2 123.2 194 85 184 183.3 111 81 149.1 29 184.1 14 91.1
#> 9.24 13.00 22.40 16.44 17.77 9.24 17.45 14.06 8.37 15.45 17.77 12.89 5.33
#> 134 96 24.1 167.1 159 91.2 26.1 58.1 150.1 6 159.1 129 55.2
#> 17.81 14.54 23.89 15.55 10.55 5.33 15.77 19.34 20.33 15.64 10.55 23.41 19.34
#> 134.1 78.1 170 181 91.3 108.1 90 36 92.1 69 136.1 70.2 179
#> 17.81 23.88 19.54 16.46 5.33 18.29 20.94 21.19 22.92 23.23 21.83 7.38 18.63
#> 97 108.2 49 26.2 60 123.3 168 184.2 157 197 170.1 71 19
#> 19.14 18.29 12.19 15.77 13.15 13.00 23.72 17.77 15.10 21.60 19.54 24.00 24.00
#> 98 20 65 38 193 80 135 151 163 156 122 21 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 27 31 80.1 161 186 82 119 80.2 103 64.1 182 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 152 185 173 53 178 185.1 65.1 95 2 19.1 22 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 102.1 182.1 38.2 1 80.3 27.1 198 161.1 44 72 2.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 87 35 82.1 132 19.2 122.1 146 118 47 103.1 196 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 72.1 161.2 11 161.3 186.1 151.1 80.4 48 151.2 19.3 11.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 65.2 146.1 64.2 156.1 19.4 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[72]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01330258 0.30653465 0.06505229
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.352186120 0.004663318 0.347750662
#> grade_iii, Cure model
#> 0.581715222
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 106 16.67 1 49 1 0
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 36 21.19 1 48 0 1
#> 56 12.21 1 60 0 0
#> 56.1 12.21 1 60 0 0
#> 127 3.53 1 62 0 1
#> 177 12.53 1 75 0 0
#> 63 22.77 1 31 1 0
#> 100 16.07 1 60 0 0
#> 58 19.34 1 39 0 0
#> 36.1 21.19 1 48 0 1
#> 68 20.62 1 44 0 0
#> 91 5.33 1 61 0 1
#> 124 9.73 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 45 17.42 1 54 0 1
#> 32 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 158 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 140 12.68 1 59 1 0
#> 157 15.10 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 114.1 13.68 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 58.1 19.34 1 39 0 0
#> 194 22.40 1 38 0 1
#> 91.1 5.33 1 61 0 1
#> 81 14.06 1 34 0 0
#> 90 20.94 1 50 0 1
#> 40 18.00 1 28 1 0
#> 101 9.97 1 10 0 1
#> 192 16.44 1 31 1 0
#> 107 11.18 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 158.1 20.14 1 74 1 0
#> 52 10.42 1 52 0 1
#> 184.1 17.77 1 38 0 0
#> 37 12.52 1 57 1 0
#> 70 7.38 1 30 1 0
#> 37.1 12.52 1 57 1 0
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 49 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 32.1 20.90 1 37 1 0
#> 97 19.14 1 65 0 1
#> 58.2 19.34 1 39 0 0
#> 175 21.91 1 43 0 0
#> 81.1 14.06 1 34 0 0
#> 181 16.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 8 18.43 1 32 0 0
#> 76 19.22 1 54 0 1
#> 78.1 23.88 1 43 0 0
#> 66.1 22.13 1 53 0 0
#> 133.1 14.65 1 57 0 0
#> 76.1 19.22 1 54 0 1
#> 5 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 140.1 12.68 1 59 1 0
#> 43 12.10 1 61 0 1
#> 58.3 19.34 1 39 0 0
#> 110 17.56 1 65 0 1
#> 117 17.46 1 26 0 1
#> 127.1 3.53 1 62 0 1
#> 6.1 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 89.1 11.44 1 NA 0 0
#> 117.1 17.46 1 26 0 1
#> 189 10.51 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 92 22.92 1 47 0 1
#> 79 16.23 1 54 1 0
#> 25 6.32 1 34 1 0
#> 164 23.60 1 76 0 1
#> 130 16.47 1 53 0 1
#> 170 19.54 1 43 0 1
#> 97.1 19.14 1 65 0 1
#> 79.1 16.23 1 54 1 0
#> 18.1 15.21 1 49 1 0
#> 177.1 12.53 1 75 0 0
#> 136 21.83 1 43 0 1
#> 25.1 6.32 1 34 1 0
#> 69 23.23 1 25 0 1
#> 63.1 22.77 1 31 1 0
#> 195 11.76 1 NA 1 0
#> 91.2 5.33 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 16 8.71 1 71 0 1
#> 199 19.81 1 NA 0 1
#> 32.2 20.90 1 37 1 0
#> 106.1 16.67 1 49 1 0
#> 130.1 16.47 1 53 0 1
#> 25.2 6.32 1 34 1 0
#> 63.2 22.77 1 31 1 0
#> 133.2 14.65 1 57 0 0
#> 140.2 12.68 1 59 1 0
#> 110.1 17.56 1 65 0 1
#> 25.3 6.32 1 34 1 0
#> 150 20.33 1 48 0 0
#> 93 10.33 1 52 0 1
#> 70.1 7.38 1 30 1 0
#> 166 19.98 1 48 0 0
#> 122 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 126 24.00 0 48 0 0
#> 104 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 165 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 147 24.00 0 76 1 0
#> 19 24.00 0 57 0 1
#> 191 24.00 0 60 0 1
#> 147.1 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 38 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 98 24.00 0 34 1 0
#> 191.1 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 53 24.00 0 32 0 1
#> 193.1 24.00 0 45 0 1
#> 193.2 24.00 0 45 0 1
#> 47 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 163 24.00 0 66 0 0
#> 102.1 24.00 0 49 0 0
#> 33 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 121 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 27 24.00 0 63 1 0
#> 27.1 24.00 0 63 1 0
#> 109.1 24.00 0 48 0 0
#> 137 24.00 0 45 1 0
#> 53.1 24.00 0 32 0 1
#> 148 24.00 0 61 1 0
#> 80 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 156 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 67.1 24.00 0 25 0 0
#> 75 24.00 0 21 1 0
#> 182.1 24.00 0 35 0 0
#> 38.1 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 27.2 24.00 0 63 1 0
#> 165.2 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 121.1 24.00 0 57 1 0
#> 38.2 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 163.1 24.00 0 66 0 0
#> 104.1 24.00 0 50 1 0
#> 119 24.00 0 17 0 0
#> 174 24.00 0 49 1 0
#> 193.3 24.00 0 45 0 1
#> 75.1 24.00 0 21 1 0
#> 200.1 24.00 0 64 0 0
#> 47.1 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 118 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 33.1 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 47.2 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 53.2 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 176.1 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 165.3 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 104.2 24.00 0 50 1 0
#> 126.1 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 72 24.00 0 40 0 1
#> 109.2 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.352 NA NA NA
#> 2 age, Cure model 0.00466 NA NA NA
#> 3 grade_ii, Cure model 0.348 NA NA NA
#> 4 grade_iii, Cure model 0.582 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0133 NA NA NA
#> 2 grade_ii, Survival model 0.307 NA NA NA
#> 3 grade_iii, Survival model 0.0651 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.352186 0.004663 0.347751 0.581715
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 257.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.352186120 0.004663318 0.347750662 0.581715222
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01330258 0.30653465 0.06505229
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8931543 0.7131497 0.8294873 0.1005407 0.4051678 0.8981941 0.8981941
#> [8] 0.9913180 0.8727078 0.2586071 0.7769953 0.5628626 0.4051678 0.5066823
#> [15] 0.9781585 0.8008734 0.6995282 0.4537731 0.4861317 0.5269353 0.7263654
#> [22] 0.4051678 0.8569313 0.8181357 0.3294334 0.6569357 0.5628626 0.3115195
#> [29] 0.9781585 0.8459811 0.4416359 0.6419449 0.9371182 0.7522025 0.9179310
#> [36] 0.7890424 0.5269353 0.9227769 0.6569357 0.8830434 0.9511589 0.8830434
#> [43] 0.6495068 0.8238239 0.8067300 0.9081099 0.9418480 0.4537731 0.6189911
#> [50] 0.5628626 0.3608857 0.8459811 0.7458021 0.5628626 0.9323832 0.6342953
#> [57] 0.6030837 0.1005407 0.3294334 0.8294873 0.6030837 0.7585460 0.7830431
#> [64] 0.8569313 0.9130389 0.5628626 0.6714941 0.6855839 0.9913180 0.7890424
#> [71] 0.3914336 0.6855839 0.6995282 0.2339017 0.7648316 0.9603161 0.1767882
#> [78] 0.7329529 0.5540058 0.6189911 0.7648316 0.8067300 0.8727078 0.3764356
#> [85] 0.9603161 0.2063041 0.2586071 0.9781585 0.4861317 0.9465234 0.4537731
#> [92] 0.7131497 0.7329529 0.9603161 0.2586071 0.8294873 0.8569313 0.6714941
#> [99] 0.9603161 0.5168974 0.9275941 0.9511589 0.5450210 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 42 106 133 78 36 56 56.1 127 177 63 100 58 36.1
#> 12.43 16.67 14.65 23.88 21.19 12.21 12.21 3.53 12.53 22.77 16.07 19.34 21.19
#> 68 91 167 45 32 190 158 171 99 140 157 66 184
#> 20.62 5.33 15.55 17.42 20.90 20.81 20.14 16.57 21.19 12.68 15.10 22.13 17.77
#> 58.1 194 91.1 81 90 40 101 192 107 6 158.1 52 184.1
#> 19.34 22.40 5.33 14.06 20.94 18.00 9.97 16.44 11.18 15.64 20.14 10.42 17.77
#> 37 70 37.1 134 180 18 49 183 32.1 97 58.2 175 81.1
#> 12.52 7.38 12.52 17.81 14.82 15.21 12.19 9.24 20.90 19.14 19.34 21.91 14.06
#> 181 55 145 8 76 78.1 66.1 133.1 76.1 5 26 140.1 43
#> 16.46 19.34 10.07 18.43 19.22 23.88 22.13 14.65 19.22 16.43 15.77 12.68 12.10
#> 58.3 110 117 127.1 6.1 197 117.1 45.1 92 79 25 164 130
#> 19.34 17.56 17.46 3.53 15.64 21.60 17.46 17.42 22.92 16.23 6.32 23.60 16.47
#> 170 97.1 79.1 18.1 177.1 136 25.1 69 63.1 91.2 190.1 16 32.2
#> 19.54 19.14 16.23 15.21 12.53 21.83 6.32 23.23 22.77 5.33 20.81 8.71 20.90
#> 106.1 130.1 25.2 63.2 133.2 140.2 110.1 25.3 150 93 70.1 166 122
#> 16.67 16.47 6.32 22.77 14.65 12.68 17.56 6.32 20.33 10.33 7.38 19.98 24.00
#> 193 126 104 162 109 1 165 67 147 19 191 147.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 200 98 191.1 182 53 193.1 193.2 47 21 35 34 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 102.1 33 31 121 27 27.1 109.1 137 53.1 148 80 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 156 95 67.1 75 182.1 38.1 22 27.2 165.2 120 120.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 38.2 95.1 163.1 104.1 119 174 193.3 75.1 200.1 47.1 196 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 103 33.1 173 47.2 135 53.2 160 103.1 176.1 46 165.3 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.2 126.1 65 62 161 72 109.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[73]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006686589 0.634508065 0.503052450
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.6538726 0.0314740 0.1175149
#> grade_iii, Cure model
#> 1.1180527
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 175 21.91 1 43 0 0
#> 5 16.43 1 51 0 1
#> 149 8.37 1 33 1 0
#> 140 12.68 1 59 1 0
#> 190 20.81 1 42 1 0
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 79 16.23 1 54 1 0
#> 110 17.56 1 65 0 1
#> 183 9.24 1 67 1 0
#> 66 22.13 1 53 0 0
#> 133 14.65 1 57 0 0
#> 171 16.57 1 41 0 1
#> 190.1 20.81 1 42 1 0
#> 30 17.43 1 78 0 0
#> 140.1 12.68 1 59 1 0
#> 168 23.72 1 70 0 0
#> 41 18.02 1 40 1 0
#> 60 13.15 1 38 1 0
#> 32 20.90 1 37 1 0
#> 113 22.86 1 34 0 0
#> 91.1 5.33 1 61 0 1
#> 158 20.14 1 74 1 0
#> 166 19.98 1 48 0 0
#> 192 16.44 1 31 1 0
#> 181 16.46 1 45 0 1
#> 49 12.19 1 48 1 0
#> 55 19.34 1 69 0 1
#> 23 16.92 1 61 0 0
#> 134 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 129 23.41 1 53 1 0
#> 26 15.77 1 49 0 1
#> 26.1 15.77 1 49 0 1
#> 96.1 14.54 1 33 0 1
#> 124 9.73 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 55.1 19.34 1 69 0 1
#> 4 17.64 1 NA 0 1
#> 49.1 12.19 1 48 1 0
#> 153 21.33 1 55 1 0
#> 57 14.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 36 21.19 1 48 0 1
#> 125 15.65 1 67 1 0
#> 150 20.33 1 48 0 0
#> 107 11.18 1 54 1 0
#> 49.2 12.19 1 48 1 0
#> 96.2 14.54 1 33 0 1
#> 26.2 15.77 1 49 0 1
#> 129.1 23.41 1 53 1 0
#> 99 21.19 1 38 0 1
#> 134.1 17.81 1 47 1 0
#> 26.3 15.77 1 49 0 1
#> 68 20.62 1 44 0 0
#> 91.2 5.33 1 61 0 1
#> 76 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 89.1 11.44 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 110.1 17.56 1 65 0 1
#> 69 23.23 1 25 0 1
#> 16 8.71 1 71 0 1
#> 88 18.37 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 16.1 8.71 1 71 0 1
#> 92 22.92 1 47 0 1
#> 26.4 15.77 1 49 0 1
#> 140.2 12.68 1 59 1 0
#> 77 7.27 1 67 0 1
#> 187.1 9.92 1 39 1 0
#> 164 23.60 1 76 0 1
#> 189 10.51 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 99.1 21.19 1 38 0 1
#> 170 19.54 1 43 0 1
#> 177 12.53 1 75 0 0
#> 49.3 12.19 1 48 1 0
#> 170.1 19.54 1 43 0 1
#> 171.1 16.57 1 41 0 1
#> 188 16.16 1 46 0 1
#> 5.1 16.43 1 51 0 1
#> 40 18.00 1 28 1 0
#> 166.1 19.98 1 48 0 0
#> 136 21.83 1 43 0 1
#> 125.1 15.65 1 67 1 0
#> 59 10.16 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 58 19.34 1 39 0 0
#> 89.2 11.44 1 NA 0 0
#> 107.2 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 91.3 5.33 1 61 0 1
#> 155 13.08 1 26 0 0
#> 49.4 12.19 1 48 1 0
#> 61 10.12 1 36 0 1
#> 188.1 16.16 1 46 0 1
#> 56 12.21 1 60 0 0
#> 81 14.06 1 34 0 0
#> 171.2 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 8 18.43 1 32 0 0
#> 4.1 17.64 1 NA 0 1
#> 157.1 15.10 1 47 0 0
#> 56.1 12.21 1 60 0 0
#> 117 17.46 1 26 0 1
#> 24.1 23.89 1 38 0 0
#> 71 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 33 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 178 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 193 24.00 0 45 0 1
#> 160 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 67.1 24.00 0 25 0 0
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 80 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 193.1 24.00 0 45 0 1
#> 87.1 24.00 0 27 0 0
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 135.1 24.00 0 58 1 0
#> 75 24.00 0 21 1 0
#> 116 24.00 0 58 0 1
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 143 24.00 0 51 0 0
#> 44.2 24.00 0 56 0 0
#> 185 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 185.1 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 31 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 33.1 24.00 0 53 0 0
#> 135.2 24.00 0 58 1 0
#> 3 24.00 0 31 1 0
#> 193.2 24.00 0 45 0 1
#> 152 24.00 0 36 0 1
#> 71.1 24.00 0 51 0 0
#> 196.1 24.00 0 19 0 0
#> 196.2 24.00 0 19 0 0
#> 146 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 162 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 65 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 103.2 24.00 0 56 1 0
#> 186 24.00 0 45 1 0
#> 143.1 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 74.1 24.00 0 43 0 1
#> 47.2 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 138.1 24.00 0 44 1 0
#> 67.2 24.00 0 25 0 0
#> 87.2 24.00 0 27 0 0
#> 28.1 24.00 0 67 1 0
#> 67.3 24.00 0 25 0 0
#> 112 24.00 0 61 0 0
#> 95 24.00 0 68 0 1
#> 3.1 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 67.4 24.00 0 25 0 0
#> 121.1 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 116.1 24.00 0 58 0 1
#> 35 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 173.1 24.00 0 19 0 1
#> 35.1 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 83.1 24.00 0 6 0 0
#> 148 24.00 0 61 1 0
#> 102 24.00 0 49 0 0
#> 82.1 24.00 0 34 0 0
#> 132.1 24.00 0 55 0 0
#> 73 24.00 0 NA 0 1
#> 174.2 24.00 0 49 1 0
#> 73.1 24.00 0 NA 0 1
#> 160.1 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 174.3 24.00 0 49 1 0
#> 138.2 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 172 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.65 NA NA NA
#> 2 age, Cure model 0.0315 NA NA NA
#> 3 grade_ii, Cure model 0.118 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00669 NA NA NA
#> 2 grade_ii, Survival model 0.635 NA NA NA
#> 3 grade_iii, Survival model 0.503 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.65387 0.03147 0.11751 1.11805
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 239.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.6538726 0.0314740 0.1175149 1.1180527
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006686589 0.634508065 0.503052450
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.98205146 0.34307836 0.71514027 0.97272551 0.86662152 0.43707654
#> [7] 0.94888852 0.82098678 0.72875791 0.62662134 0.95853665 0.32680573
#> [13] 0.81506894 0.67258359 0.43707654 0.65751491 0.86662152 0.14896649
#> [19] 0.58501756 0.84968033 0.42503691 0.29321298 0.98205146 0.48098871
#> [25] 0.49141960 0.70116996 0.69403590 0.89886439 0.53112757 0.66507074
#> [31] 0.60225198 0.80323653 0.21868467 0.74859712 0.74859712 0.82098678
#> [37] 0.86101448 0.53112757 0.89886439 0.37430098 0.83821970 0.70116996
#> [43] 0.38850894 0.77922096 0.47006175 0.92924544 0.89886439 0.82098678
#> [49] 0.74859712 0.21868467 0.38850894 0.60225198 0.74859712 0.45903782
#> [55] 0.98205146 0.55821057 0.31018129 0.61848298 0.79124462 0.79726578
#> [61] 0.62662134 0.25729397 0.96332575 0.57612711 0.96332575 0.27599062
#> [67] 0.74859712 0.86662152 0.97740615 0.94888852 0.18927770 0.92924544
#> [73] 0.38850894 0.51173719 0.88277390 0.89886439 0.51173719 0.67258359
#> [79] 0.73549099 0.71514027 0.59371446 0.49141960 0.35909806 0.77922096
#> [85] 0.06858677 0.53112757 0.92924544 0.92416978 0.98205146 0.85535097
#> [91] 0.89886439 0.94397967 0.73549099 0.88816964 0.84395498 0.67258359
#> [97] 0.64989916 0.56718572 0.80323653 0.88816964 0.64216888 0.06858677
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 91 175 5 149 140 190 187 96 79 110 183 66 133
#> 5.33 21.91 16.43 8.37 12.68 20.81 9.92 14.54 16.23 17.56 9.24 22.13 14.65
#> 171 190.1 30 140.1 168 41 60 32 113 91.1 158 166 192
#> 16.57 20.81 17.43 12.68 23.72 18.02 13.15 20.90 22.86 5.33 20.14 19.98 16.44
#> 181 49 55 23 134 157 129 26 26.1 96.1 123 55.1 49.1
#> 16.46 12.19 19.34 16.92 17.81 15.10 23.41 15.77 15.77 14.54 13.00 19.34 12.19
#> 153 57 85 36 125 150 107 49.2 96.2 26.2 129.1 99 134.1
#> 21.33 14.46 16.44 21.19 15.65 20.33 11.18 12.19 14.54 15.77 23.41 21.19 17.81
#> 26.3 68 91.2 76 15 184 6 39 110.1 69 16 88 16.1
#> 15.77 20.62 5.33 19.22 22.68 17.77 15.64 15.59 17.56 23.23 8.71 18.37 8.71
#> 92 26.4 140.2 77 187.1 164 107.1 99.1 170 177 49.3 170.1 171.1
#> 22.92 15.77 12.68 7.27 9.92 23.60 11.18 21.19 19.54 12.53 12.19 19.54 16.57
#> 188 5.1 40 166.1 136 125.1 24 58 107.2 43 91.3 155 49.4
#> 16.16 16.43 18.00 19.98 21.83 15.65 23.89 19.34 11.18 12.10 5.33 13.08 12.19
#> 61 188.1 56 81 171.2 111 8 157.1 56.1 117 24.1 71 53
#> 10.12 16.16 12.21 14.06 16.57 17.45 18.43 15.10 12.21 17.46 23.89 24.00 24.00
#> 33 28 178 67 193 160 135 87 67.1 174 174.1 80 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 193.1 87.1 103 47 44 135.1 75 116 83 138 44.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.2 185 82 185.1 103.1 31 132 33.1 135.2 3 193.2 152 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 196.2 146 1 162 65 74 103.2 186 143.1 47.1 74.1 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 138.1 67.2 87.2 28.1 67.3 112 95 3.1 173 67.4 121.1 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 35 151.1 173.1 35.1 141 83.1 148 102 82.1 132.1 174.2 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 174.3 138.2 198 172
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[74]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001399503 0.516613046 0.516027298
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.002980789 0.001728955 -0.261800337
#> grade_iii, Cure model
#> 0.785088274
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 26 15.77 1 49 0 1
#> 16 8.71 1 71 0 1
#> 166 19.98 1 48 0 0
#> 181 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 105 19.75 1 60 0 0
#> 39 15.59 1 37 0 1
#> 63 22.77 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 129 23.41 1 53 1 0
#> 68 20.62 1 44 0 0
#> 111 17.45 1 47 0 1
#> 128 20.35 1 35 0 1
#> 175 21.91 1 43 0 0
#> 128.1 20.35 1 35 0 1
#> 26.1 15.77 1 49 0 1
#> 129.1 23.41 1 53 1 0
#> 68.1 20.62 1 44 0 0
#> 56 12.21 1 60 0 0
#> 113 22.86 1 34 0 0
#> 88 18.37 1 47 0 0
#> 169 22.41 1 46 0 0
#> 78 23.88 1 43 0 0
#> 66 22.13 1 53 0 0
#> 68.2 20.62 1 44 0 0
#> 69 23.23 1 25 0 1
#> 166.1 19.98 1 48 0 0
#> 8 18.43 1 32 0 0
#> 39.1 15.59 1 37 0 1
#> 177.1 12.53 1 75 0 0
#> 88.1 18.37 1 47 0 0
#> 183 9.24 1 67 1 0
#> 123 13.00 1 44 1 0
#> 51 18.23 1 83 0 1
#> 85 16.44 1 36 0 0
#> 25 6.32 1 34 1 0
#> 49 12.19 1 48 1 0
#> 125 15.65 1 67 1 0
#> 96 14.54 1 33 0 1
#> 194 22.40 1 38 0 1
#> 175.1 21.91 1 43 0 0
#> 108 18.29 1 39 0 1
#> 110 17.56 1 65 0 1
#> 14 12.89 1 21 0 0
#> 124 9.73 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 8.1 18.43 1 32 0 0
#> 23 16.92 1 61 0 0
#> 101 9.97 1 10 0 1
#> 155 13.08 1 26 0 0
#> 167 15.55 1 56 1 0
#> 155.1 13.08 1 26 0 0
#> 167.1 15.55 1 56 1 0
#> 86 23.81 1 58 0 1
#> 169.1 22.41 1 46 0 0
#> 58 19.34 1 39 0 0
#> 166.2 19.98 1 48 0 0
#> 92 22.92 1 47 0 1
#> 154 12.63 1 20 1 0
#> 8.2 18.43 1 32 0 0
#> 23.1 16.92 1 61 0 0
#> 63.1 22.77 1 31 1 0
#> 167.2 15.55 1 56 1 0
#> 18 15.21 1 49 1 0
#> 190 20.81 1 42 1 0
#> 51.1 18.23 1 83 0 1
#> 113.1 22.86 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 37 12.52 1 57 1 0
#> 187 9.92 1 39 1 0
#> 78.1 23.88 1 43 0 0
#> 55 19.34 1 69 0 1
#> 93 10.33 1 52 0 1
#> 167.3 15.55 1 56 1 0
#> 195 11.76 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 93.1 10.33 1 52 0 1
#> 175.2 21.91 1 43 0 0
#> 26.2 15.77 1 49 0 1
#> 43 12.10 1 61 0 1
#> 86.1 23.81 1 58 0 1
#> 139 21.49 1 63 1 0
#> 70 7.38 1 30 1 0
#> 78.2 23.88 1 43 0 0
#> 114.1 13.68 1 NA 0 0
#> 70.1 7.38 1 30 1 0
#> 13 14.34 1 54 0 1
#> 37.1 12.52 1 57 1 0
#> 197 21.60 1 69 1 0
#> 77 7.27 1 67 0 1
#> 51.2 18.23 1 83 0 1
#> 189 10.51 1 NA 1 0
#> 129.2 23.41 1 53 1 0
#> 199 19.81 1 NA 0 1
#> 129.3 23.41 1 53 1 0
#> 170 19.54 1 43 0 1
#> 106 16.67 1 49 1 0
#> 76 19.22 1 54 0 1
#> 171 16.57 1 41 0 1
#> 66.1 22.13 1 53 0 0
#> 90 20.94 1 50 0 1
#> 192 16.44 1 31 1 0
#> 168 23.72 1 70 0 0
#> 49.1 12.19 1 48 1 0
#> 18.1 15.21 1 49 1 0
#> 97 19.14 1 65 0 1
#> 100 16.07 1 60 0 0
#> 61 10.12 1 36 0 1
#> 55.1 19.34 1 69 0 1
#> 154.1 12.63 1 20 1 0
#> 118 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 120 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 185 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 142 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 182 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 103 24.00 0 56 1 0
#> 120.1 24.00 0 68 0 1
#> 71.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 118.1 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 178.1 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 73 24.00 0 NA 0 1
#> 160.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 27 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 148 24.00 0 61 1 0
#> 138.1 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 144.1 24.00 0 28 0 1
#> 165 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 46.1 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 2 24.00 0 9 0 0
#> 95 24.00 0 68 0 1
#> 162.1 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 135 24.00 0 58 1 0
#> 174 24.00 0 49 1 0
#> 12.1 24.00 0 63 0 0
#> 54 24.00 0 53 1 0
#> 174.1 24.00 0 49 1 0
#> 2.1 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 160.2 24.00 0 31 1 0
#> 162.2 24.00 0 51 0 0
#> 120.2 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 22.1 24.00 0 52 1 0
#> 135.1 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 138.2 24.00 0 44 1 0
#> 34.1 24.00 0 36 0 0
#> 54.1 24.00 0 53 1 0
#> 143 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 82 24.00 0 34 0 0
#> 28 24.00 0 67 1 0
#> 38 24.00 0 31 1 0
#> 178.2 24.00 0 52 1 0
#> 138.3 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 193 24.00 0 45 0 1
#> 160.3 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 83.1 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 131.1 24.00 0 66 0 0
#> 143.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.00298 NA NA NA
#> 2 age, Cure model 0.00173 NA NA NA
#> 3 grade_ii, Cure model -0.262 NA NA NA
#> 4 grade_iii, Cure model 0.785 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00140 NA NA NA
#> 2 grade_ii, Survival model 0.517 NA NA NA
#> 3 grade_iii, Survival model 0.516 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.002981 0.001729 -0.261800 0.785088
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 256.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.002980789 0.001728955 -0.261800337 0.785088274
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001399503 0.516613046 0.516027298
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.69496011 0.95707674 0.42711609 0.66111917 0.85266495 0.45525021
#> [7] 0.72783334 0.21389949 0.12382610 0.37944830 0.61782227 0.40823001
#> [13] 0.29830308 0.40823001 0.69496011 0.12382610 0.37944830 0.88299888
#> [19] 0.19157043 0.55570072 0.24568520 0.02636611 0.27745644 0.37944830
#> [25] 0.16825206 0.42711609 0.52877962 0.72783334 0.85266495 0.55570072
#> [31] 0.94980200 0.82199465 0.58288869 0.66964940 0.98578373 0.89058384
#> [37] 0.71958105 0.79095550 0.26688787 0.29830308 0.57383389 0.60904363
#> [43] 0.82972253 0.23490461 0.52877962 0.62653055 0.93516024 0.80652816
#> [49] 0.74402864 0.80652816 0.74402864 0.07625675 0.24568520 0.47432602
#> [55] 0.42711609 0.18012556 0.83745249 0.52877962 0.62653055 0.21389949
#> [61] 0.74402864 0.77532584 0.36009886 0.58288869 0.19157043 0.47432602
#> [67] 0.86790450 0.94249782 0.02636611 0.47432602 0.91302363 0.74402864
#> [73] 0.99290556 0.36009886 0.91302363 0.29830308 0.69496011 0.90554519
#> [79] 0.07625675 0.33967435 0.96432301 0.02636611 0.96432301 0.79876283
#> [85] 0.86790450 0.32920872 0.97863098 0.58288869 0.12382610 0.12382610
#> [91] 0.46484461 0.64386525 0.51047489 0.65252540 0.27745644 0.34997034
#> [97] 0.66964940 0.10694033 0.89058384 0.77532584 0.51966994 0.68648277
#> [103] 0.92778493 0.47432602 0.83745249 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 26 16 166 181 177 105 39 63 129 68 111 128 175
#> 15.77 8.71 19.98 16.46 12.53 19.75 15.59 22.77 23.41 20.62 17.45 20.35 21.91
#> 128.1 26.1 129.1 68.1 56 113 88 169 78 66 68.2 69 166.1
#> 20.35 15.77 23.41 20.62 12.21 22.86 18.37 22.41 23.88 22.13 20.62 23.23 19.98
#> 8 39.1 177.1 88.1 183 123 51 85 25 49 125 96 194
#> 18.43 15.59 12.53 18.37 9.24 13.00 18.23 16.44 6.32 12.19 15.65 14.54 22.40
#> 175.1 108 110 14 15 8.1 23 101 155 167 155.1 167.1 86
#> 21.91 18.29 17.56 12.89 22.68 18.43 16.92 9.97 13.08 15.55 13.08 15.55 23.81
#> 169.1 58 166.2 92 154 8.2 23.1 63.1 167.2 18 190 51.1 113.1
#> 22.41 19.34 19.98 22.92 12.63 18.43 16.92 22.77 15.55 15.21 20.81 18.23 22.86
#> 58.1 37 187 78.1 55 93 167.3 91 190.1 93.1 175.2 26.2 43
#> 19.34 12.52 9.92 23.88 19.34 10.33 15.55 5.33 20.81 10.33 21.91 15.77 12.10
#> 86.1 139 70 78.2 70.1 13 37.1 197 77 51.2 129.2 129.3 170
#> 23.81 21.49 7.38 23.88 7.38 14.34 12.52 21.60 7.27 18.23 23.41 23.41 19.54
#> 106 76 171 66.1 90 192 168 49.1 18.1 97 100 61 55.1
#> 16.67 19.22 16.57 22.13 20.94 16.44 23.72 12.19 15.21 19.14 16.07 10.12 19.34
#> 154.1 118 71 178 138 152 34 65 186 144 120 160 141
#> 12.63 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 185 131 53 142 64 182 173 103 120.1 71.1 83 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 178.1 33 160.1 46 22 27 62 12 148 138.1 27.1 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 144.1 165 17 162 165.1 46.1 35 161 2 95 162.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 174 12.1 54 174.1 2.1 122 116 160.2 162.2 120.2 137 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 87 138.2 34.1 54.1 143 191 82 28 38 178.2 138.3 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 160.3 137.1 121 94 198 83.1 119 131.1 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[75]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007538107 0.366345391 -0.326558436
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.11989113 0.01287543 0.70068157
#> grade_iii, Cure model
#> 1.08528374
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 16 8.71 1 71 0 1
#> 123 13.00 1 44 1 0
#> 159 10.55 1 50 0 1
#> 100 16.07 1 60 0 0
#> 79 16.23 1 54 1 0
#> 187 9.92 1 39 1 0
#> 57 14.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 16.1 8.71 1 71 0 1
#> 4 17.64 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 18 15.21 1 49 1 0
#> 36 21.19 1 48 0 1
#> 194 22.40 1 38 0 1
#> 108 18.29 1 39 0 1
#> 57.1 14.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 192 16.44 1 31 1 0
#> 136 21.83 1 43 0 1
#> 139 21.49 1 63 1 0
#> 32 20.90 1 37 1 0
#> 134 17.81 1 47 1 0
#> 8 18.43 1 32 0 0
#> 111 17.45 1 47 0 1
#> 134.1 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 195 11.76 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 14 12.89 1 21 0 0
#> 13 14.34 1 54 0 1
#> 159.1 10.55 1 50 0 1
#> 164 23.60 1 76 0 1
#> 130 16.47 1 53 0 1
#> 145.1 10.07 1 65 1 0
#> 32.1 20.90 1 37 1 0
#> 123.1 13.00 1 44 1 0
#> 4.1 17.64 1 NA 0 1
#> 111.1 17.45 1 47 0 1
#> 192.1 16.44 1 31 1 0
#> 69 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 123.2 13.00 1 44 1 0
#> 114 13.68 1 NA 0 0
#> 150.1 20.33 1 48 0 0
#> 4.2 17.64 1 NA 0 1
#> 81 14.06 1 34 0 0
#> 25 6.32 1 34 1 0
#> 199 19.81 1 NA 0 1
#> 194.1 22.40 1 38 0 1
#> 108.1 18.29 1 39 0 1
#> 171 16.57 1 41 0 1
#> 58 19.34 1 39 0 0
#> 92 22.92 1 47 0 1
#> 123.3 13.00 1 44 1 0
#> 55.1 19.34 1 69 0 1
#> 29 15.45 1 68 1 0
#> 117 17.46 1 26 0 1
#> 158 20.14 1 74 1 0
#> 4.3 17.64 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 149 8.37 1 33 1 0
#> 88 18.37 1 47 0 0
#> 40 18.00 1 28 1 0
#> 45 17.42 1 54 0 1
#> 108.2 18.29 1 39 0 1
#> 89 11.44 1 NA 0 0
#> 194.2 22.40 1 38 0 1
#> 181 16.46 1 45 0 1
#> 55.2 19.34 1 69 0 1
#> 59 10.16 1 NA 1 0
#> 57.2 14.46 1 45 0 1
#> 89.1 11.44 1 NA 0 0
#> 111.2 17.45 1 47 0 1
#> 197 21.60 1 69 1 0
#> 30 17.43 1 78 0 0
#> 15 22.68 1 48 0 0
#> 114.1 13.68 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 179 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 108.3 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 149.1 8.37 1 33 1 0
#> 134.2 17.81 1 47 1 0
#> 91 5.33 1 61 0 1
#> 86 23.81 1 58 0 1
#> 36.1 21.19 1 48 0 1
#> 187.1 9.92 1 39 1 0
#> 194.3 22.40 1 38 0 1
#> 60 13.15 1 38 1 0
#> 5 16.43 1 51 0 1
#> 110 17.56 1 65 0 1
#> 164.1 23.60 1 76 0 1
#> 29.1 15.45 1 68 1 0
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 60.1 13.15 1 38 1 0
#> 195.1 11.76 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 8.2 18.43 1 32 0 0
#> 41 18.02 1 40 1 0
#> 167.1 15.55 1 56 1 0
#> 190.1 20.81 1 42 1 0
#> 70 7.38 1 30 1 0
#> 90 20.94 1 50 0 1
#> 180.1 14.82 1 37 0 0
#> 158.1 20.14 1 74 1 0
#> 190.2 20.81 1 42 1 0
#> 97 19.14 1 65 0 1
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 19 24.00 0 57 0 1
#> 173 24.00 0 19 0 1
#> 176 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 200 24.00 0 64 0 0
#> 9 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 186 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 82 24.00 0 34 0 0
#> 72 24.00 0 40 0 1
#> 115 24.00 0 NA 1 0
#> 104 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 17.1 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#> 27 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 19.1 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 176.1 24.00 0 43 0 1
#> 27.1 24.00 0 63 1 0
#> 176.2 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 72.1 24.00 0 40 0 1
#> 160 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 142 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 160.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 80.1 24.00 0 41 0 0
#> 71.1 24.00 0 51 0 0
#> 19.2 24.00 0 57 0 1
#> 196.1 24.00 0 19 0 0
#> 31.1 24.00 0 36 0 1
#> 80.2 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 173.1 24.00 0 19 0 1
#> 1 24.00 0 23 1 0
#> 12.1 24.00 0 63 0 0
#> 102.1 24.00 0 49 0 0
#> 174.1 24.00 0 49 1 0
#> 12.2 24.00 0 63 0 0
#> 121.1 24.00 0 57 1 0
#> 141.1 24.00 0 44 1 0
#> 196.2 24.00 0 19 0 0
#> 191 24.00 0 60 0 1
#> 98 24.00 0 34 1 0
#> 11 24.00 0 42 0 1
#> 104.1 24.00 0 50 1 0
#> 176.3 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 121.2 24.00 0 57 1 0
#> 118.1 24.00 0 44 1 0
#> 27.2 24.00 0 63 1 0
#> 142.1 24.00 0 53 0 0
#> 47.1 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 1.1 24.00 0 23 1 0
#> 137.1 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.12 NA NA NA
#> 2 age, Cure model 0.0129 NA NA NA
#> 3 grade_ii, Cure model 0.701 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00754 NA NA NA
#> 2 grade_ii, Survival model 0.366 NA NA NA
#> 3 grade_iii, Survival model -0.327 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.11989 0.01288 0.70068 1.08528
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 247.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.11989113 0.01287543 0.70068157 1.08528374
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007538107 0.366345391 -0.326558436
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2791355640 0.8919552647 0.7354049090 0.8125495981 0.5220555018
#> [6] 0.4979597642 0.8654948265 0.6449570905 0.8389736111 0.8919552647
#> [11] 0.4159149263 0.5828636672 0.0517508014 0.0152837919 0.2406073781
#> [16] 0.6449570905 0.1449781053 0.1371597024 0.4626434391 0.0327601560
#> [21] 0.0453091624 0.0730987493 0.3102496756 0.2040196891 0.3612082817
#> [26] 0.3102496756 0.6075674753 0.2040196891 0.7863545076 0.6831455503
#> [31] 0.8125495981 0.0008927680 0.4389700440 0.8389736111 0.0730987493
#> [36] 0.7354049090 0.3612082817 0.4626434391 0.0042618101 0.1076884671
#> [41] 0.7354049090 0.1076884671 0.6962492582 0.9727673364 0.0152837919
#> [46] 0.2406073781 0.4273693519 0.1449781053 0.0072606075 0.7354049090
#> [51] 0.1449781053 0.5584980352 0.3506234394 0.1222684762 0.5342763194
#> [56] 0.9188770161 0.2310908654 0.2999266161 0.4045756241 0.2406073781
#> [61] 0.0152837919 0.4507311855 0.1449781053 0.6449570905 0.3612082817
#> [66] 0.0389617085 0.3933991684 0.0110460456 0.1769525589 0.0873830534
#> [71] 0.1948399262 0.6323385904 0.2406073781 0.9591801428 0.9188770161
#> [76] 0.3102496756 0.9863324914 0.0001043736 0.0517508014 0.8654948265
#> [81] 0.0152837919 0.7094089669 0.4859931291 0.3401670839 0.0008927680
#> [86] 0.5584980352 0.5951773311 0.5099378964 0.7094089669 0.7994454669
#> [91] 0.2040196891 0.2895435660 0.5342763194 0.0873830534 0.9457007661
#> [96] 0.0654296486 0.6075674753 0.1222684762 0.0873830534 0.1857761085
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000
#>
#> $Time
#> 51 16 123 159 100 79 187 57 145 16.1 23 18 36
#> 18.23 8.71 13.00 10.55 16.07 16.23 9.92 14.46 10.07 8.71 16.92 15.21 21.19
#> 194 108 57.1 55 105 192 136 139 32 134 8 111 134.1
#> 22.40 18.29 14.46 19.34 19.75 16.44 21.83 21.49 20.90 17.81 18.43 17.45 17.81
#> 180 8.1 14 13 159.1 164 130 145.1 32.1 123.1 111.1 192.1 69
#> 14.82 18.43 12.89 14.34 10.55 23.60 16.47 10.07 20.90 13.00 17.45 16.44 23.23
#> 150 123.2 150.1 81 25 194.1 108.1 171 58 92 123.3 55.1 29
#> 20.33 13.00 20.33 14.06 6.32 22.40 18.29 16.57 19.34 22.92 13.00 19.34 15.45
#> 117 158 167 149 88 40 45 108.2 194.2 181 55.2 57.2 111.2
#> 17.46 20.14 15.55 8.37 18.37 18.00 17.42 18.29 22.40 16.46 19.34 14.46 17.45
#> 197 30 15 76 190 179 96 108.3 77 149.1 134.2 91 86
#> 21.60 17.43 22.68 19.22 20.81 18.63 14.54 18.29 7.27 8.37 17.81 5.33 23.81
#> 36.1 187.1 194.3 60 5 110 164.1 29.1 157 188 60.1 37 8.2
#> 21.19 9.92 22.40 13.15 16.43 17.56 23.60 15.45 15.10 16.16 13.15 12.52 18.43
#> 41 167.1 190.1 70 90 180.1 158.1 190.2 97 141 31 109 22
#> 18.02 15.55 20.81 7.38 20.94 14.82 20.14 20.81 19.14 24.00 24.00 24.00 24.00
#> 80 156 135 19 173 176 112 200 9 12 102 186 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 82 72 104 165 71 17 17.1 135.1 27 87 19.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 27.1 176.2 137 131 144 54 198 72.1 160 120 121 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 160.1 95 163 161 3 162 196 80.1 71.1 19.2 196.1 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.2 47 173.1 1 12.1 102.1 174.1 12.2 121.1 141.1 196.2 191 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 104.1 176.3 64 38 118 53 121.2 118.1 27.2 142.1 47.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 1.1 137.1 116
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[76]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0004352338 0.3830069898 0.1969190478
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.18127869 -0.01122036 0.44506364
#> grade_iii, Cure model
#> 1.29846446
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 76 19.22 1 54 0 1
#> 63 22.77 1 31 1 0
#> 30 17.43 1 78 0 0
#> 99 21.19 1 38 0 1
#> 93 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 183 9.24 1 67 1 0
#> 51 18.23 1 83 0 1
#> 40 18.00 1 28 1 0
#> 114 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 81 14.06 1 34 0 0
#> 181 16.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 134 17.81 1 47 1 0
#> 97.1 19.14 1 65 0 1
#> 157 15.10 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 110 17.56 1 65 0 1
#> 154 12.63 1 20 1 0
#> 25 6.32 1 34 1 0
#> 85 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 153 21.33 1 55 1 0
#> 81.1 14.06 1 34 0 0
#> 81.2 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 40.1 18.00 1 28 1 0
#> 15 22.68 1 48 0 0
#> 149 8.37 1 33 1 0
#> 181.1 16.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 40.2 18.00 1 28 1 0
#> 52 10.42 1 52 0 1
#> 164 23.60 1 76 0 1
#> 130 16.47 1 53 0 1
#> 90 20.94 1 50 0 1
#> 124 9.73 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 107 11.18 1 54 1 0
#> 93.1 10.33 1 52 0 1
#> 149.1 8.37 1 33 1 0
#> 136 21.83 1 43 0 1
#> 159 10.55 1 50 0 1
#> 43 12.10 1 61 0 1
#> 76.1 19.22 1 54 0 1
#> 134.1 17.81 1 47 1 0
#> 124.1 9.73 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 68.1 20.62 1 44 0 0
#> 123.1 13.00 1 44 1 0
#> 63.1 22.77 1 31 1 0
#> 85.1 16.44 1 36 0 0
#> 145 10.07 1 65 1 0
#> 4 17.64 1 NA 0 1
#> 10.1 10.53 1 34 0 0
#> 134.2 17.81 1 47 1 0
#> 41 18.02 1 40 1 0
#> 92 22.92 1 47 0 1
#> 79.1 16.23 1 54 1 0
#> 5 16.43 1 51 0 1
#> 99.1 21.19 1 38 0 1
#> 63.2 22.77 1 31 1 0
#> 81.3 14.06 1 34 0 0
#> 97.2 19.14 1 65 0 1
#> 89 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 130.1 16.47 1 53 0 1
#> 45 17.42 1 54 0 1
#> 111 17.45 1 47 0 1
#> 24 23.89 1 38 0 0
#> 181.2 16.46 1 45 0 1
#> 16 8.71 1 71 0 1
#> 101.1 9.97 1 10 0 1
#> 61 10.12 1 36 0 1
#> 6 15.64 1 39 0 0
#> 69.1 23.23 1 25 0 1
#> 51.1 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 105 19.75 1 60 0 0
#> 45.1 17.42 1 54 0 1
#> 197 21.60 1 69 1 0
#> 14 12.89 1 21 0 0
#> 69.2 23.23 1 25 0 1
#> 145.1 10.07 1 65 1 0
#> 23 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 29 15.45 1 68 1 0
#> 197.1 21.60 1 69 1 0
#> 130.2 16.47 1 53 0 1
#> 169 22.41 1 46 0 0
#> 59 10.16 1 NA 1 0
#> 149.2 8.37 1 33 1 0
#> 36 21.19 1 48 0 1
#> 175 21.91 1 43 0 0
#> 89.1 11.44 1 NA 0 0
#> 197.2 21.60 1 69 1 0
#> 192 16.44 1 31 1 0
#> 56 12.21 1 60 0 0
#> 117 17.46 1 26 0 1
#> 101.2 9.97 1 10 0 1
#> 194 22.40 1 38 0 1
#> 81.4 14.06 1 34 0 0
#> 63.3 22.77 1 31 1 0
#> 123.2 13.00 1 44 1 0
#> 57 14.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 190 20.81 1 42 1 0
#> 168 23.72 1 70 0 0
#> 185 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 2 24.00 0 9 0 0
#> 148 24.00 0 61 1 0
#> 38 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 162 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 120 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 62 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 87 24.00 0 27 0 0
#> 9 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 163 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 9.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 176 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 182 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 182.1 24.00 0 35 0 0
#> 71 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 122 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 82.1 24.00 0 34 0 0
#> 22 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 132 24.00 0 55 0 0
#> 71.1 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 19.1 24.00 0 57 0 1
#> 160.1 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 112.1 24.00 0 61 0 0
#> 122.1 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 182.2 24.00 0 35 0 0
#> 38.1 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 47.1 24.00 0 38 0 1
#> 20.1 24.00 0 46 1 0
#> 143.1 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 73.2 24.00 0 NA 0 1
#> 98.1 24.00 0 34 1 0
#> 28 24.00 0 67 1 0
#> 160.2 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 185.1 24.00 0 44 1 0
#> 121.1 24.00 0 57 1 0
#> 142.1 24.00 0 53 0 0
#> 2.1 24.00 0 9 0 0
#> 103 24.00 0 56 1 0
#> 196 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 148.1 24.00 0 61 1 0
#> 135 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 143.2 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 112.2 24.00 0 61 0 0
#> 178 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 9.2 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 163.1 24.00 0 66 0 0
#> 95.1 24.00 0 68 0 1
#> 103.1 24.00 0 56 1 0
#> 21 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.181 NA NA NA
#> 2 age, Cure model -0.0112 NA NA NA
#> 3 grade_ii, Cure model 0.445 NA NA NA
#> 4 grade_iii, Cure model 1.30 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000435 NA NA NA
#> 2 grade_ii, Survival model 0.383 NA NA NA
#> 3 grade_iii, Survival model 0.197 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.18128 -0.01122 0.44506 1.29846
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 245.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.18127869 -0.01122036 0.44506364 1.29846446
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0004352338 0.3830069898 0.1969190478
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.856646729 0.921287020 0.377562711 0.135602295 0.535124034 0.277721682
#> [7] 0.881028696 0.027566709 0.953020119 0.425590046 0.454225586 0.397070685
#> [13] 0.733346019 0.605510671 0.357605346 0.481532192 0.397070685 0.716493635
#> [19] 0.082214935 0.508179038 0.807420677 0.992193063 0.631292727 0.682541136
#> [25] 0.267140368 0.733346019 0.733346019 0.945058624 0.454225586 0.177984153
#> [31] 0.968875027 0.605510671 0.665567375 0.454225586 0.872885621 0.064470642
#> [37] 0.579514043 0.307630782 0.774509013 0.840319680 0.881028696 0.968875027
#> [43] 0.224635111 0.848490722 0.832114120 0.377562711 0.481532192 0.337944445
#> [49] 0.337944445 0.774509013 0.135602295 0.631292727 0.905282287 0.856646729
#> [55] 0.481532192 0.444671638 0.121220601 0.665567375 0.656929783 0.277721682
#> [61] 0.135602295 0.733346019 0.397070685 0.317876544 0.579514043 0.544080411
#> [67] 0.526172660 0.009973509 0.605510671 0.960953478 0.921287020 0.897183000
#> [73] 0.691060820 0.082214935 0.425590046 0.708059953 0.367580529 0.544080411
#> [79] 0.236128065 0.799127866 0.082214935 0.905282287 0.561736622 0.570638907
#> [85] 0.699582274 0.236128065 0.579514043 0.189699620 0.968875027 0.277721682
#> [91] 0.213026456 0.236128065 0.631292727 0.823893504 0.517191806 0.921287020
#> [97] 0.201429671 0.733346019 0.135602295 0.774509013 0.724929328 0.815675003
#> [103] 0.327978027 0.045855730 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 10 101 76 63 30 99 93 78 183 51 40 97 81
#> 10.53 9.97 19.22 22.77 17.43 21.19 10.33 23.88 9.24 18.23 18.00 19.14 14.06
#> 181 150 134 97.1 157 69 110 154 25 85 188 153 81.1
#> 16.46 20.33 17.81 19.14 15.10 23.23 17.56 12.63 6.32 16.44 16.16 21.33 14.06
#> 81.2 187 40.1 15 149 181.1 79 40.2 52 164 130 90 123
#> 14.06 9.92 18.00 22.68 8.37 16.46 16.23 18.00 10.42 23.60 16.47 20.94 13.00
#> 107 93.1 149.1 136 159 43 76.1 134.1 68 68.1 123.1 63.1 85.1
#> 11.18 10.33 8.37 21.83 10.55 12.10 19.22 17.81 20.62 20.62 13.00 22.77 16.44
#> 145 10.1 134.2 41 92 79.1 5 99.1 63.2 81.3 97.2 32 130.1
#> 10.07 10.53 17.81 18.02 22.92 16.23 16.43 21.19 22.77 14.06 19.14 20.90 16.47
#> 45 111 24 181.2 16 101.1 61 6 69.1 51.1 18 105 45.1
#> 17.42 17.45 23.89 16.46 8.71 9.97 10.12 15.64 23.23 18.23 15.21 19.75 17.42
#> 197 14 69.2 145.1 23 171 29 197.1 130.2 169 149.2 36 175
#> 21.60 12.89 23.23 10.07 16.92 16.57 15.45 21.60 16.47 22.41 8.37 21.19 21.91
#> 197.2 192 56 117 101.2 194 81.4 63.3 123.2 57 37 190 168
#> 21.60 16.44 12.21 17.46 9.97 22.40 14.06 22.77 13.00 14.46 12.52 20.81 23.72
#> 185 20 2 148 38 35 35.1 65 131 142 75 143 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 120 160 191 62 141 95 116 87 9 191.1 163 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 82 176 116.1 182 146 182.1 71 19 122 82.1 22 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 132 71.1 121 47 19.1 160.1 112 112.1 122.1 27 182.2 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 47.1 20.1 143.1 80 98.1 28 160.2 173 109 152 185.1 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 2.1 103 196 200 148.1 135 1 143.2 54 112.2 178 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 146.1 163.1 95.1 103.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[77]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02873545 0.89922629 0.35124602
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.562557938 -0.007729407 -0.399264127
#> grade_iii, Cure model
#> 0.184556447
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 166 19.98 1 48 0 0
#> 108 18.29 1 39 0 1
#> 153 21.33 1 55 1 0
#> 4 17.64 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 51 18.23 1 83 0 1
#> 10 10.53 1 34 0 0
#> 164 23.60 1 76 0 1
#> 175 21.91 1 43 0 0
#> 99 21.19 1 38 0 1
#> 4.1 17.64 1 NA 0 1
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 29 15.45 1 68 1 0
#> 150 20.33 1 48 0 0
#> 49 12.19 1 48 1 0
#> 199 19.81 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 14 12.89 1 21 0 0
#> 86 23.81 1 58 0 1
#> 37 12.52 1 57 1 0
#> 189 10.51 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 150.1 20.33 1 48 0 0
#> 187 9.92 1 39 1 0
#> 179 18.63 1 42 0 0
#> 133 14.65 1 57 0 0
#> 59 10.16 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 187.1 9.92 1 39 1 0
#> 6 15.64 1 39 0 0
#> 129 23.41 1 53 1 0
#> 78 23.88 1 43 0 0
#> 70 7.38 1 30 1 0
#> 192 16.44 1 31 1 0
#> 175.1 21.91 1 43 0 0
#> 15 22.68 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 6.1 15.64 1 39 0 0
#> 190 20.81 1 42 1 0
#> 175.2 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 58 19.34 1 39 0 0
#> 170 19.54 1 43 0 1
#> 125 15.65 1 67 1 0
#> 89.1 11.44 1 NA 0 0
#> 181 16.46 1 45 0 1
#> 76 19.22 1 54 0 1
#> 170.1 19.54 1 43 0 1
#> 8 18.43 1 32 0 0
#> 6.2 15.64 1 39 0 0
#> 23 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 26.1 15.77 1 49 0 1
#> 134 17.81 1 47 1 0
#> 187.2 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 136 21.83 1 43 0 1
#> 6.3 15.64 1 39 0 0
#> 5 16.43 1 51 0 1
#> 25 6.32 1 34 1 0
#> 60 13.15 1 38 1 0
#> 8.1 18.43 1 32 0 0
#> 89.2 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 184 17.77 1 38 0 0
#> 36 21.19 1 48 0 1
#> 93 10.33 1 52 0 1
#> 99.1 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 129.1 23.41 1 53 1 0
#> 195 11.76 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 58.1 19.34 1 39 0 0
#> 114.1 13.68 1 NA 0 0
#> 188 16.16 1 46 0 1
#> 114.2 13.68 1 NA 0 0
#> 78.1 23.88 1 43 0 0
#> 181.1 16.46 1 45 0 1
#> 18 15.21 1 49 1 0
#> 30 17.43 1 78 0 0
#> 99.2 21.19 1 38 0 1
#> 39.1 15.59 1 37 0 1
#> 25.1 6.32 1 34 1 0
#> 25.2 6.32 1 34 1 0
#> 140 12.68 1 59 1 0
#> 42 12.43 1 49 0 1
#> 90 20.94 1 50 0 1
#> 101.1 9.97 1 10 0 1
#> 110 17.56 1 65 0 1
#> 159 10.55 1 50 0 1
#> 86.1 23.81 1 58 0 1
#> 187.3 9.92 1 39 1 0
#> 158 20.14 1 74 1 0
#> 68.1 20.62 1 44 0 0
#> 85 16.44 1 36 0 0
#> 23.1 16.92 1 61 0 0
#> 180 14.82 1 37 0 0
#> 153.1 21.33 1 55 1 0
#> 23.2 16.92 1 61 0 0
#> 32 20.90 1 37 1 0
#> 101.2 9.97 1 10 0 1
#> 59.1 10.16 1 NA 1 0
#> 175.3 21.91 1 43 0 0
#> 88.1 18.37 1 47 0 0
#> 55 19.34 1 69 0 1
#> 29.1 15.45 1 68 1 0
#> 26.2 15.77 1 49 0 1
#> 89.3 11.44 1 NA 0 0
#> 36.1 21.19 1 48 0 1
#> 64 24.00 0 43 0 0
#> 7 24.00 0 37 1 0
#> 185 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 160 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 33 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 172 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 74 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 7.1 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 11 24.00 0 42 0 1
#> 186 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 193.1 24.00 0 45 0 1
#> 83 24.00 0 6 0 0
#> 54 24.00 0 53 1 0
#> 138 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 71.1 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 193.2 24.00 0 45 0 1
#> 172.2 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 72.1 24.00 0 40 0 1
#> 147 24.00 0 76 1 0
#> 151.1 24.00 0 42 0 0
#> 193.3 24.00 0 45 0 1
#> 172.3 24.00 0 41 0 0
#> 103.1 24.00 0 56 1 0
#> 94 24.00 0 51 0 1
#> 75.1 24.00 0 21 1 0
#> 112 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 121 24.00 0 57 1 0
#> 28.1 24.00 0 67 1 0
#> 193.4 24.00 0 45 0 1
#> 126 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 193.5 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 65 24.00 0 57 1 0
#> 146 24.00 0 63 1 0
#> 54.1 24.00 0 53 1 0
#> 9 24.00 0 31 1 0
#> 193.6 24.00 0 45 0 1
#> 121.1 24.00 0 57 1 0
#> 71.2 24.00 0 51 0 0
#> 71.3 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 103.2 24.00 0 56 1 0
#> 11.1 24.00 0 42 0 1
#> 146.1 24.00 0 63 1 0
#> 83.1 24.00 0 6 0 0
#> 62.1 24.00 0 71 0 0
#> 182.1 24.00 0 35 0 0
#> 62.2 24.00 0 71 0 0
#> 191.1 24.00 0 60 0 1
#> 73 24.00 0 NA 0 1
#> 186.1 24.00 0 45 1 0
#> 121.2 24.00 0 57 1 0
#> 7.2 24.00 0 37 1 0
#> 28.2 24.00 0 67 1 0
#> 148.1 24.00 0 61 1 0
#> 87 24.00 0 27 0 0
#> 72.2 24.00 0 40 0 1
#> 178 24.00 0 52 1 0
#> 148.2 24.00 0 61 1 0
#> 141.1 24.00 0 44 1 0
#> 103.3 24.00 0 56 1 0
#> 31 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 151.2 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.563 NA NA NA
#> 2 age, Cure model -0.00773 NA NA NA
#> 3 grade_ii, Cure model -0.399 NA NA NA
#> 4 grade_iii, Cure model 0.185 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0287 NA NA NA
#> 2 grade_ii, Survival model 0.899 NA NA NA
#> 3 grade_iii, Survival model 0.351 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.562558 -0.007729 -0.399264 0.184556
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.8
#> Residual Deviance: 252.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.562557938 -0.007729407 -0.399264127 0.184556447
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02873545 0.89922629 0.35124602
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.287106e-01 4.239220e-02 1.030921e-01 7.372110e-03 7.102160e-01
#> [6] 1.099051e-01 6.458990e-01 3.338840e-04 2.453603e-03 1.035112e-02
#> [11] 3.738059e-01 2.676972e-02 4.215191e-01 3.237197e-02 6.050015e-01
#> [16] 4.051853e-01 5.274722e-01 8.434344e-05 5.654914e-01 2.518462e-01
#> [21] 3.237197e-02 8.211078e-01 7.332776e-02 4.905330e-01 7.552793e-01
#> [26] 8.211078e-01 3.160443e-01 6.205034e-04 9.521574e-06 9.095443e-01
#> [31] 1.965955e-01 2.453603e-03 1.813060e-03 6.458990e-01 3.160443e-01
#> [36] 2.421259e-02 2.453603e-03 2.640546e-01 5.430770e-02 4.621797e-02
#> [41] 3.023209e-01 1.762996e-01 6.811034e-02 4.621797e-02 7.881908e-02
#> [46] 3.160443e-01 1.486342e-01 2.640546e-01 1.171062e-01 8.211078e-01
#> [51] 7.325327e-01 6.006392e-03 3.160443e-01 2.175817e-01 9.324866e-01
#> [56] 5.089438e-01 7.881908e-02 9.035284e-02 1.244718e-01 1.035112e-02
#> [61] 6.882411e-01 1.035112e-02 1.306734e-03 6.205034e-04 4.835934e-07
#> [66] 5.430770e-02 2.401053e-01 9.521574e-06 1.762996e-01 4.552237e-01
#> [71] 1.401699e-01 1.035112e-02 3.738059e-01 9.324866e-01 9.324866e-01
#> [76] 5.463002e-01 5.850289e-01 1.928042e-02 7.552793e-01 1.321390e-01
#> [81] 6.252288e-01 8.434344e-05 8.211078e-01 3.880848e-02 2.676972e-02
#> [86] 1.965955e-01 1.486342e-01 4.726625e-01 7.372110e-03 1.486342e-01
#> [91] 2.172521e-02 7.552793e-01 2.453603e-03 9.035284e-02 5.430770e-02
#> [96] 4.215191e-01 2.640546e-01 1.035112e-02 0.000000e+00 0.000000e+00
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 79 166 108 153 61 51 10 164 175 99 39 68 29
#> 16.23 19.98 18.29 21.33 10.12 18.23 10.53 23.60 21.91 21.19 15.59 20.62 15.45
#> 150 49 167 14 86 37 100 150.1 187 179 133 101 187.1
#> 20.33 12.19 15.55 12.89 23.81 12.52 16.07 20.33 9.92 18.63 14.65 9.97 9.92
#> 6 129 78 70 192 175.1 15 10.1 6.1 190 175.2 26 58
#> 15.64 23.41 23.88 7.38 16.44 21.91 22.68 10.53 15.64 20.81 21.91 15.77 19.34
#> 170 125 181 76 170.1 8 6.2 23 26.1 134 187.2 145 136
#> 19.54 15.65 16.46 19.22 19.54 18.43 15.64 16.92 15.77 17.81 9.92 10.07 21.83
#> 6.3 5 25 60 8.1 88 184 36 93 99.1 92 129.1 24
#> 15.64 16.43 6.32 13.15 18.43 18.37 17.77 21.19 10.33 21.19 22.92 23.41 23.89
#> 58.1 188 78.1 181.1 18 30 99.2 39.1 25.1 25.2 140 42 90
#> 19.34 16.16 23.88 16.46 15.21 17.43 21.19 15.59 6.32 6.32 12.68 12.43 20.94
#> 101.1 110 159 86.1 187.3 158 68.1 85 23.1 180 153.1 23.2 32
#> 9.97 17.56 10.55 23.81 9.92 20.14 20.62 16.44 16.92 14.82 21.33 16.92 20.90
#> 101.2 175.3 88.1 55 29.1 26.2 36.1 64 7 185 148 160 165
#> 9.97 21.91 18.37 19.34 15.45 15.77 21.19 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 72 172 21 163 193 104 143 75 103 74 165.1 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 11 186 95 193.1 83 54 138 172.1 71 62 28 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 141 193.2 172.2 27 72.1 147 151.1 193.3 172.3 103.1 94 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 116 121 28.1 193.4 126 182 193.5 191 120 65 146 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 193.6 121.1 71.2 71.3 80 17 103.2 11.1 146.1 83.1 62.1 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 191.1 186.1 121.2 7.2 28.2 148.1 87 72.2 178 148.2 141.1 103.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 31.1 151.2
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[78]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001668541 0.276147082 0.402536201
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.992234882 0.021634953 -0.005310466
#> grade_iii, Cure model
#> 0.743558525
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 63 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 184 17.77 1 38 0 0
#> 129 23.41 1 53 1 0
#> 85 16.44 1 36 0 0
#> 50 10.02 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 127 3.53 1 62 0 1
#> 45 17.42 1 54 0 1
#> 158 20.14 1 74 1 0
#> 106 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 15 22.68 1 48 0 0
#> 91 5.33 1 61 0 1
#> 180 14.82 1 37 0 0
#> 199 19.81 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 127.1 3.53 1 62 0 1
#> 55 19.34 1 69 0 1
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 97 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 181 16.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 150 20.33 1 48 0 0
#> 32 20.90 1 37 1 0
#> 15.1 22.68 1 48 0 0
#> 139.1 21.49 1 63 1 0
#> 199.1 19.81 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 24 23.89 1 38 0 0
#> 55.1 19.34 1 69 0 1
#> 123 13.00 1 44 1 0
#> 113 22.86 1 34 0 0
#> 26 15.77 1 49 0 1
#> 45.1 17.42 1 54 0 1
#> 52 10.42 1 52 0 1
#> 15.2 22.68 1 48 0 0
#> 149 8.37 1 33 1 0
#> 77 7.27 1 67 0 1
#> 37 12.52 1 57 1 0
#> 166 19.98 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 66 22.13 1 53 0 0
#> 128 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 37.1 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 150.1 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 77.1 7.27 1 67 0 1
#> 78 23.88 1 43 0 0
#> 187 9.92 1 39 1 0
#> 159 10.55 1 50 0 1
#> 18 15.21 1 49 1 0
#> 134.1 17.81 1 47 1 0
#> 158.1 20.14 1 74 1 0
#> 188 16.16 1 46 0 1
#> 93 10.33 1 52 0 1
#> 134.2 17.81 1 47 1 0
#> 91.1 5.33 1 61 0 1
#> 130 16.47 1 53 0 1
#> 36 21.19 1 48 0 1
#> 90.1 20.94 1 50 0 1
#> 90.2 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 18.1 15.21 1 49 1 0
#> 113.1 22.86 1 34 0 0
#> 10 10.53 1 34 0 0
#> 86.1 23.81 1 58 0 1
#> 70 7.38 1 30 1 0
#> 100 16.07 1 60 0 0
#> 56 12.21 1 60 0 0
#> 127.2 3.53 1 62 0 1
#> 184.1 17.77 1 38 0 0
#> 18.2 15.21 1 49 1 0
#> 153 21.33 1 55 1 0
#> 189 10.51 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 18.3 15.21 1 49 1 0
#> 107 11.18 1 54 1 0
#> 166.1 19.98 1 48 0 0
#> 167 15.55 1 56 1 0
#> 57 14.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 89 11.44 1 NA 0 0
#> 100.1 16.07 1 60 0 0
#> 81 14.06 1 34 0 0
#> 179 18.63 1 42 0 0
#> 10.1 10.53 1 34 0 0
#> 155 13.08 1 26 0 0
#> 18.4 15.21 1 49 1 0
#> 183 9.24 1 67 1 0
#> 197.1 21.60 1 69 1 0
#> 129.1 23.41 1 53 1 0
#> 184.2 17.77 1 38 0 0
#> 170 19.54 1 43 0 1
#> 149.1 8.37 1 33 1 0
#> 139.2 21.49 1 63 1 0
#> 100.2 16.07 1 60 0 0
#> 169 22.41 1 46 0 0
#> 199.2 19.81 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 184.3 17.77 1 38 0 0
#> 61 10.12 1 36 0 1
#> 108.1 18.29 1 39 0 1
#> 194 22.40 1 38 0 1
#> 56.1 12.21 1 60 0 0
#> 107.1 11.18 1 54 1 0
#> 123.1 13.00 1 44 1 0
#> 32.1 20.90 1 37 1 0
#> 115 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 135 24.00 0 58 1 0
#> 72 24.00 0 40 0 1
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 12.1 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 104 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 185 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 163 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 28 24.00 0 67 1 0
#> 131 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 182 24.00 0 35 0 0
#> 33.1 24.00 0 53 0 0
#> 176 24.00 0 43 0 1
#> 143.1 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 178 24.00 0 52 1 0
#> 3 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 1 24.00 0 23 1 0
#> 144.1 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 122 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 143.2 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 185.2 24.00 0 44 1 0
#> 11.1 24.00 0 42 0 1
#> 1.1 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 87 24.00 0 27 0 0
#> 3.1 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 163.2 24.00 0 66 0 0
#> 73.2 24.00 0 NA 0 1
#> 47.1 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 118 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 137.2 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 22.2 24.00 0 52 1 0
#> 173.1 24.00 0 19 0 1
#> 34 24.00 0 36 0 0
#> 135.1 24.00 0 58 1 0
#> 48 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 12.2 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 1.2 24.00 0 23 1 0
#> 19.1 24.00 0 57 0 1
#> 1.3 24.00 0 23 1 0
#> 71.1 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 186.1 24.00 0 45 1 0
#> 196.1 24.00 0 19 0 0
#> 80.1 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 87.1 24.00 0 27 0 0
#> 160 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 94 24.00 0 51 0 1
#> 162 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.992 NA NA NA
#> 2 age, Cure model 0.0216 NA NA NA
#> 3 grade_ii, Cure model -0.00531 NA NA NA
#> 4 grade_iii, Cure model 0.744 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00167 NA NA NA
#> 2 grade_ii, Survival model 0.276 NA NA NA
#> 3 grade_iii, Survival model 0.403 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99223 0.02163 -0.00531 0.74356
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 250.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.992234882 0.021634953 -0.005310466 0.743558525
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001668541 0.276147082 0.402536201
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.15949749 0.28450675 0.57165579 0.10352039 0.65510660 0.51086428
#> [7] 0.97937450 0.60517447 0.41818085 0.63026838 0.26098953 0.18557446
#> [13] 0.96538066 0.75762290 0.54623001 0.97937450 0.46551207 0.48369936
#> [19] 0.50181930 0.64689295 0.07164937 0.39876675 0.36912124 0.18557446
#> [25] 0.28450675 0.77307254 0.01756479 0.46551207 0.80379655 0.13167050
#> [31] 0.69550894 0.60517447 0.88599346 0.18557446 0.92977824 0.95125252
#> [37] 0.81893278 0.43716229 0.75762290 0.24839814 0.38889812 0.90801812
#> [43] 0.81893278 0.33922240 0.39876675 0.51989622 0.95125252 0.04490100
#> [49] 0.91529611 0.86379447 0.71953885 0.54623001 0.41818085 0.66331388
#> [55] 0.89337220 0.54623001 0.96538066 0.63861495 0.32832943 0.33922240
#> [61] 0.33922240 0.62187396 0.71953885 0.13167050 0.87122011 0.07164937
#> [67] 0.94409022 0.67145918 0.83394429 0.97937450 0.57165579 0.71953885
#> [73] 0.31720763 0.15949749 0.71953885 0.84892741 0.43716229 0.71157009
#> [79] 0.78079137 0.53744298 0.67145918 0.78846376 0.49276537 0.87122011
#> [85] 0.79613179 0.71953885 0.92255064 0.26098953 0.10352039 0.57165579
#> [91] 0.45607538 0.92977824 0.28450675 0.67145918 0.22268121 0.70356124
#> [97] 0.57165579 0.90071267 0.51989622 0.23574761 0.83394429 0.84892741
#> [103] 0.80379655 0.36912124 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 63 139 184 129 85 88 127 45 158 106 197 15 91
#> 22.77 21.49 17.77 23.41 16.44 18.37 3.53 17.42 20.14 16.67 21.60 22.68 5.33
#> 180 134 127.1 55 97 8 181 86 150 32 15.1 139.1 96
#> 14.82 17.81 3.53 19.34 19.14 18.43 16.46 23.81 20.33 20.90 22.68 21.49 14.54
#> 24 55.1 123 113 26 45.1 52 15.2 149 77 37 166 180.1
#> 23.89 19.34 13.00 22.86 15.77 17.42 10.42 22.68 8.37 7.27 12.52 19.98 14.82
#> 66 128 145 37.1 90 150.1 108 77.1 78 187 159 18 134.1
#> 22.13 20.35 10.07 12.52 20.94 20.33 18.29 7.27 23.88 9.92 10.55 15.21 17.81
#> 158.1 188 93 134.2 91.1 130 36 90.1 90.2 23 18.1 113.1 10
#> 20.14 16.16 10.33 17.81 5.33 16.47 21.19 20.94 20.94 16.92 15.21 22.86 10.53
#> 86.1 70 100 56 127.2 184.1 18.2 153 63.1 18.3 107 166.1 167
#> 23.81 7.38 16.07 12.21 3.53 17.77 15.21 21.33 22.77 15.21 11.18 19.98 15.55
#> 57 41 100.1 81 179 10.1 155 18.4 183 197.1 129.1 184.2 170
#> 14.46 18.02 16.07 14.06 18.63 10.53 13.08 15.21 9.24 21.60 23.41 17.77 19.54
#> 149.1 139.2 100.2 169 125 184.3 61 108.1 194 56.1 107.1 123.1 32.1
#> 8.37 21.49 16.07 22.41 15.65 17.77 10.12 18.29 22.40 12.21 11.18 13.00 20.90
#> 12 143 174 135 72 82 144 12.1 193 191 104 11 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 163 138 83 33 200 28 131 185.1 46 137 182 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 143.1 103 178 3 22 22.1 196 1 144.1 151 122 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 27 143.2 185.2 11.1 1.1 47 147 44 87 3.1 67 163.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 19 118 186 137.1 137.2 141 22.2 173.1 34 135.1 48 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 12.2 21 121 148 1.2 19.1 1.3 71.1 148.1 186.1 196.1 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 87.1 160 54 94 162
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[79]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006101184 0.317148976 0.224006023
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.57087320 0.01102233 0.12046813
#> grade_iii, Cure model
#> 0.43348221
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 125 15.65 1 67 1 0
#> 128 20.35 1 35 0 1
#> 89 11.44 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 55 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 23 16.92 1 61 0 0
#> 189 10.51 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 167 15.55 1 56 1 0
#> 60 13.15 1 38 1 0
#> 167.1 15.55 1 56 1 0
#> 136 21.83 1 43 0 1
#> 97 19.14 1 65 0 1
#> 167.2 15.55 1 56 1 0
#> 93 10.33 1 52 0 1
#> 39 15.59 1 37 0 1
#> 56 12.21 1 60 0 0
#> 41 18.02 1 40 1 0
#> 37 12.52 1 57 1 0
#> 8 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 49 12.19 1 48 1 0
#> 113 22.86 1 34 0 0
#> 155 13.08 1 26 0 0
#> 59 10.16 1 NA 1 0
#> 167.3 15.55 1 56 1 0
#> 23.1 16.92 1 61 0 0
#> 29 15.45 1 68 1 0
#> 30 17.43 1 78 0 0
#> 108 18.29 1 39 0 1
#> 88 18.37 1 47 0 0
#> 133 14.65 1 57 0 0
#> 86 23.81 1 58 0 1
#> 101 9.97 1 10 0 1
#> 159 10.55 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 63 22.77 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 59.1 10.16 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 93.1 10.33 1 52 0 1
#> 23.2 16.92 1 61 0 0
#> 164 23.60 1 76 0 1
#> 16 8.71 1 71 0 1
#> 24 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 149 8.37 1 33 1 0
#> 133.1 14.65 1 57 0 0
#> 50 10.02 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 50.1 10.02 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 50.2 10.02 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 110 17.56 1 65 0 1
#> 58 19.34 1 39 0 0
#> 79 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 56.1 12.21 1 60 0 0
#> 23.3 16.92 1 61 0 0
#> 129 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 180 14.82 1 37 0 0
#> 18 15.21 1 49 1 0
#> 139 21.49 1 63 1 0
#> 136.1 21.83 1 43 0 1
#> 51 18.23 1 83 0 1
#> 133.2 14.65 1 57 0 0
#> 150 20.33 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 153 21.33 1 55 1 0
#> 41.1 18.02 1 40 1 0
#> 59.2 10.16 1 NA 1 0
#> 190.1 20.81 1 42 1 0
#> 41.2 18.02 1 40 1 0
#> 50.3 10.02 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 181.1 16.46 1 45 0 1
#> 108.1 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 49.1 12.19 1 48 1 0
#> 69 23.23 1 25 0 1
#> 57.1 14.46 1 45 0 1
#> 66 22.13 1 53 0 0
#> 134 17.81 1 47 1 0
#> 6 15.64 1 39 0 0
#> 24.1 23.89 1 38 0 0
#> 105 19.75 1 60 0 0
#> 32 20.90 1 37 1 0
#> 68 20.62 1 44 0 0
#> 77 7.27 1 67 0 1
#> 140.1 12.68 1 59 1 0
#> 127 3.53 1 62 0 1
#> 125.1 15.65 1 67 1 0
#> 124.1 9.73 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 16.1 8.71 1 71 0 1
#> 123 13.00 1 44 1 0
#> 101.1 9.97 1 10 0 1
#> 56.2 12.21 1 60 0 0
#> 153.1 21.33 1 55 1 0
#> 195 11.76 1 NA 1 0
#> 134.1 17.81 1 47 1 0
#> 8.1 18.43 1 32 0 0
#> 50.4 10.02 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 90 20.94 1 50 0 1
#> 39.1 15.59 1 37 0 1
#> 18.1 15.21 1 49 1 0
#> 8.2 18.43 1 32 0 0
#> 147 24.00 0 76 1 0
#> 9 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 142 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 141 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 94 24.00 0 51 0 1
#> 138 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 35 24.00 0 51 0 0
#> 27.1 24.00 0 63 1 0
#> 131 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 17 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 64.1 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 161 24.00 0 45 0 0
#> 2 24.00 0 9 0 0
#> 142.2 24.00 0 53 0 0
#> 161.1 24.00 0 45 0 0
#> 73 24.00 0 NA 0 1
#> 47 24.00 0 38 0 1
#> 161.2 24.00 0 45 0 0
#> 22 24.00 0 52 1 0
#> 147.1 24.00 0 76 1 0
#> 186.1 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 22.1 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 7.1 24.00 0 37 1 0
#> 126 24.00 0 48 0 0
#> 7.2 24.00 0 37 1 0
#> 148 24.00 0 61 1 0
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 152 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 72 24.00 0 40 0 1
#> 17.1 24.00 0 38 0 1
#> 94.1 24.00 0 51 0 1
#> 161.3 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 3 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 22.2 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 156 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 102.1 24.00 0 49 0 0
#> 35.1 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 95.1 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 182.1 24.00 0 35 0 0
#> 156.1 24.00 0 50 1 0
#> 75 24.00 0 21 1 0
#> 121.1 24.00 0 57 1 0
#> 143.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 116.1 24.00 0 58 0 1
#> 62.1 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 163 24.00 0 66 0 0
#> 94.2 24.00 0 51 0 1
#> 17.2 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.571 NA NA NA
#> 2 age, Cure model 0.0110 NA NA NA
#> 3 grade_ii, Cure model 0.120 NA NA NA
#> 4 grade_iii, Cure model 0.433 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00610 NA NA NA
#> 2 grade_ii, Survival model 0.317 NA NA NA
#> 3 grade_iii, Survival model 0.224 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.57087 0.01102 0.12047 0.43348
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.8
#> Residual Deviance: 253.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.57087320 0.01102233 0.12046813 0.43348221
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006101184 0.317148976 0.224006023
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.68821065 0.37897712 0.91691651 0.43375193 0.96224953 0.62259709
#> [7] 0.68010958 0.72727811 0.83548778 0.72727811 0.25203821 0.45449404
#> [13] 0.72727811 0.93657458 0.71180303 0.88374338 0.53371510 0.87696684
#> [19] 0.46478196 0.40137204 0.90371597 0.18496203 0.84250797 0.72727811
#> [25] 0.62259709 0.75674252 0.60549161 0.50461242 0.49455159 0.79304245
#> [31] 0.09980048 0.94944068 0.92350192 0.20277067 0.58784743 0.40137204
#> [37] 0.93657458 0.62259709 0.12590276 0.96864372 0.04515513 0.93005475
#> [43] 0.98123592 0.79304245 0.65553391 0.87014050 0.60549161 0.59672560
#> [49] 0.43375193 0.67194468 0.85648251 0.88374338 0.62259709 0.14758599
#> [55] 0.34480330 0.77862509 0.76413981 0.28081941 0.25203821 0.52408234
#> [61] 0.79304245 0.39022923 0.77862509 0.29484849 0.53371510 0.34480330
#> [67] 0.53371510 0.21960623 0.65553391 0.50461242 0.81432962 0.90371597
#> [73] 0.16675090 0.81432962 0.23603453 0.57015601 0.70392517 0.04515513
#> [79] 0.42294677 0.33260897 0.36753864 0.98752483 0.85648251 0.99377859
#> [85] 0.68821065 0.82842418 0.96864372 0.84951811 0.94944068 0.88374338
#> [91] 0.29484849 0.57015601 0.46478196 0.56100325 0.32008365 0.71180303
#> [97] 0.76413981 0.46478196 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 125 128 43 55 187 23 188 167 60 167.1 136 97 167.2
#> 15.65 20.35 12.10 19.34 9.92 16.92 16.16 15.55 13.15 15.55 21.83 19.14 15.55
#> 93 39 56 41 37 8 166 49 113 155 167.3 23.1 29
#> 10.33 15.59 12.21 18.02 12.52 18.43 19.98 12.19 22.86 13.08 15.55 16.92 15.45
#> 30 108 88 133 86 101 159 63 184 166.1 93.1 23.2 164
#> 17.43 18.29 18.37 14.65 23.81 9.97 10.55 22.77 17.77 19.98 10.33 16.92 23.60
#> 16 24 52 149 133.1 181 154 30.1 110 58 79 140 56.1
#> 8.71 23.89 10.42 8.37 14.65 16.46 12.63 17.43 17.56 19.34 16.23 12.68 12.21
#> 23.3 129 190 180 18 139 136.1 51 133.2 150 180.1 153 41.1
#> 16.92 23.41 20.81 14.82 15.21 21.49 21.83 18.23 14.65 20.33 14.82 21.33 18.02
#> 190.1 41.2 169 181.1 108.1 57 49.1 69 57.1 66 134 6 24.1
#> 20.81 18.02 22.41 16.46 18.29 14.46 12.19 23.23 14.46 22.13 17.81 15.64 23.89
#> 105 32 68 77 140.1 127 125.1 81 16.1 123 101.1 56.2 153.1
#> 19.75 20.90 20.62 7.27 12.68 3.53 15.65 14.06 8.71 13.00 9.97 12.21 21.33
#> 134.1 8.1 40 90 39.1 18.1 8.2 147 9 31 64 142 104
#> 17.81 18.43 18.00 20.94 15.59 15.21 18.43 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 146 67 141 27 118 142.1 7 94 138 174 109 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 27.1 131 87 116 17 186 64.1 121 161 2 142.2 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 161.2 22 147.1 186.1 65 22.1 193 103 7.1 126 7.2 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 62 119 152 102 185 47.1 74 28 72 17.1 94.1 161.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 67.1 3 122 22.2 19 156 176 172 71 174.1 102.1 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 95.1 34 182.1 156.1 75 121.1 143.1 83 116.1 62.1 82 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.2 17.2 162
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[80]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00297735 0.70218665 0.21867620
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.344662019 0.005591139 -0.168585462
#> grade_iii, Cure model
#> 1.056541564
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 183 9.24 1 67 1 0
#> 86 23.81 1 58 0 1
#> 50 10.02 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 192 16.44 1 31 1 0
#> 85.1 16.44 1 36 0 0
#> 14 12.89 1 21 0 0
#> 89 11.44 1 NA 0 0
#> 136.1 21.83 1 43 0 1
#> 42 12.43 1 49 0 1
#> 50.1 10.02 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 153 21.33 1 55 1 0
#> 4 17.64 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 159 10.55 1 50 0 1
#> 149 8.37 1 33 1 0
#> 97 19.14 1 65 0 1
#> 117 17.46 1 26 0 1
#> 79 16.23 1 54 1 0
#> 192.1 16.44 1 31 1 0
#> 158 20.14 1 74 1 0
#> 93 10.33 1 52 0 1
#> 36 21.19 1 48 0 1
#> 52 10.42 1 52 0 1
#> 130 16.47 1 53 0 1
#> 79.1 16.23 1 54 1 0
#> 157 15.10 1 47 0 0
#> 55 19.34 1 69 0 1
#> 79.2 16.23 1 54 1 0
#> 117.1 17.46 1 26 0 1
#> 68 20.62 1 44 0 0
#> 5 16.43 1 51 0 1
#> 125 15.65 1 67 1 0
#> 91 5.33 1 61 0 1
#> 93.1 10.33 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 10 10.53 1 34 0 0
#> 86.1 23.81 1 58 0 1
#> 130.1 16.47 1 53 0 1
#> 86.2 23.81 1 58 0 1
#> 85.2 16.44 1 36 0 0
#> 56 12.21 1 60 0 0
#> 93.2 10.33 1 52 0 1
#> 58 19.34 1 39 0 0
#> 179 18.63 1 42 0 0
#> 52.2 10.42 1 52 0 1
#> 26 15.77 1 49 0 1
#> 125.1 15.65 1 67 1 0
#> 136.2 21.83 1 43 0 1
#> 157.1 15.10 1 47 0 0
#> 175 21.91 1 43 0 0
#> 96 14.54 1 33 0 1
#> 99 21.19 1 38 0 1
#> 61 10.12 1 36 0 1
#> 155 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 77 7.27 1 67 0 1
#> 128 20.35 1 35 0 1
#> 136.3 21.83 1 43 0 1
#> 111 17.45 1 47 0 1
#> 77.1 7.27 1 67 0 1
#> 140 12.68 1 59 1 0
#> 6 15.64 1 39 0 0
#> 133 14.65 1 57 0 0
#> 68.1 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 39 15.59 1 37 0 1
#> 168 23.72 1 70 0 0
#> 199 19.81 1 NA 0 1
#> 26.1 15.77 1 49 0 1
#> 78 23.88 1 43 0 0
#> 69 23.23 1 25 0 1
#> 175.1 21.91 1 43 0 0
#> 99.1 21.19 1 38 0 1
#> 154 12.63 1 20 1 0
#> 14.1 12.89 1 21 0 0
#> 175.2 21.91 1 43 0 0
#> 40 18.00 1 28 1 0
#> 39.1 15.59 1 37 0 1
#> 105 19.75 1 60 0 0
#> 60.1 13.15 1 38 1 0
#> 134 17.81 1 47 1 0
#> 133.1 14.65 1 57 0 0
#> 39.2 15.59 1 37 0 1
#> 56.1 12.21 1 60 0 0
#> 30 17.43 1 78 0 0
#> 49 12.19 1 48 1 0
#> 49.1 12.19 1 48 1 0
#> 50.2 10.02 1 NA 1 0
#> 117.2 17.46 1 26 0 1
#> 158.1 20.14 1 74 1 0
#> 15 22.68 1 48 0 0
#> 90 20.94 1 50 0 1
#> 124 9.73 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 110 17.56 1 65 0 1
#> 99.2 21.19 1 38 0 1
#> 78.1 23.88 1 43 0 0
#> 150.1 20.33 1 48 0 0
#> 14.2 12.89 1 21 0 0
#> 56.2 12.21 1 60 0 0
#> 166 19.98 1 48 0 0
#> 36.1 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 52.3 10.42 1 52 0 1
#> 183.1 9.24 1 67 1 0
#> 110.1 17.56 1 65 0 1
#> 37 12.52 1 57 1 0
#> 154.1 12.63 1 20 1 0
#> 122 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 75 24.00 0 21 1 0
#> 31 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 3 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 2 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 186 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 19 24.00 0 57 0 1
#> 87 24.00 0 27 0 0
#> 46.1 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 142 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 2.1 24.00 0 9 0 0
#> 135 24.00 0 58 1 0
#> 34 24.00 0 36 0 0
#> 162.1 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 38.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 22 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 147.1 24.00 0 76 1 0
#> 75.1 24.00 0 21 1 0
#> 94.1 24.00 0 51 0 1
#> 38.2 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 22.1 24.00 0 52 1 0
#> 142.1 24.00 0 53 0 0
#> 3.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#> 115 24.00 0 NA 1 0
#> 143.1 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 83 24.00 0 6 0 0
#> 1 24.00 0 23 1 0
#> 116 24.00 0 58 0 1
#> 178 24.00 0 52 1 0
#> 46.2 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 31.1 24.00 0 36 0 1
#> 94.2 24.00 0 51 0 1
#> 17.1 24.00 0 38 0 1
#> 103.1 24.00 0 56 1 0
#> 3.2 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 28 24.00 0 67 1 0
#> 141.1 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 141.2 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 115.1 24.00 0 NA 1 0
#> 33.1 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 94.3 24.00 0 51 0 1
#> 109.1 24.00 0 48 0 0
#> 31.2 24.00 0 36 0 1
#> 44.1 24.00 0 56 0 0
#> 126 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 172 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.345 NA NA NA
#> 2 age, Cure model 0.00559 NA NA NA
#> 3 grade_ii, Cure model -0.169 NA NA NA
#> 4 grade_iii, Cure model 1.06 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00298 NA NA NA
#> 2 grade_ii, Survival model 0.702 NA NA NA
#> 3 grade_iii, Survival model 0.219 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.344662 0.005591 -0.168585 1.056542
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 248 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.344662019 0.005591139 -0.168585462 1.056541564
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00297735 0.70218665 0.21867620
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.94339257 0.03611743 0.13949560 0.71799785 0.51391041 0.51391041
#> [7] 0.51391041 0.74386507 0.13949560 0.80337830 0.29580610 0.19444257
#> [13] 0.95960416 0.86149969 0.96774398 0.37767218 0.44733849 0.56843937
#> [19] 0.51391041 0.31671495 0.91064923 0.20548100 0.87805973 0.49485977
#> [25] 0.56843937 0.66524735 0.35733321 0.56843937 0.44733849 0.26447068
#> [31] 0.55910413 0.61290369 0.99192219 0.91064923 0.87805973 0.86977592
#> [37] 0.03611743 0.49485977 0.03611743 0.51391041 0.81174898 0.91064923
#> [43] 0.35733321 0.38797525 0.87805973 0.59506120 0.61290369 0.13949560
#> [49] 0.66524735 0.10446523 0.70033979 0.20548100 0.93515883 0.73520365
#> [55] 0.70917210 0.97582742 0.28526149 0.13949560 0.47561476 0.97582742
#> [61] 0.76960190 0.63041328 0.68275837 0.26447068 0.85321771 0.63924327
#> [67] 0.06661395 0.59506120 0.01159058 0.07935742 0.10446523 0.20548100
#> [73] 0.77821103 0.74386507 0.10446523 0.40843797 0.63924327 0.34704351
#> [79] 0.71799785 0.41835469 0.68275837 0.63924327 0.81174898 0.48521749
#> [85] 0.83672813 0.83672813 0.44733849 0.31671495 0.09179585 0.25396642
#> [91] 0.18293859 0.42809716 0.20548100 0.01159058 0.29580610 0.74386507
#> [97] 0.81174898 0.33680351 0.20548100 0.39831060 0.87805973 0.94339257
#> [103] 0.42809716 0.79500104 0.77821103 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 183 86 136 60 85 192 85.1 14 136.1 42 150 153 16
#> 9.24 23.81 21.83 13.15 16.44 16.44 16.44 12.89 21.83 12.43 20.33 21.33 8.71
#> 159 149 97 117 79 192.1 158 93 36 52 130 79.1 157
#> 10.55 8.37 19.14 17.46 16.23 16.44 20.14 10.33 21.19 10.42 16.47 16.23 15.10
#> 55 79.2 117.1 68 5 125 91 93.1 52.1 10 86.1 130.1 86.2
#> 19.34 16.23 17.46 20.62 16.43 15.65 5.33 10.33 10.42 10.53 23.81 16.47 23.81
#> 85.2 56 93.2 58 179 52.2 26 125.1 136.2 157.1 175 96 99
#> 16.44 12.21 10.33 19.34 18.63 10.42 15.77 15.65 21.83 15.10 21.91 14.54 21.19
#> 61 155 13 77 128 136.3 111 77.1 140 6 133 68.1 43
#> 10.12 13.08 14.34 7.27 20.35 21.83 17.45 7.27 12.68 15.64 14.65 20.62 12.10
#> 39 168 26.1 78 69 175.1 99.1 154 14.1 175.2 40 39.1 105
#> 15.59 23.72 15.77 23.88 23.23 21.91 21.19 12.63 12.89 21.91 18.00 15.59 19.75
#> 60.1 134 133.1 39.2 56.1 30 49 49.1 117.2 158.1 15 90 197
#> 13.15 17.81 14.65 15.59 12.21 17.43 12.19 12.19 17.46 20.14 22.68 20.94 21.60
#> 110 99.2 78.1 150.1 14.2 56.2 166 36.1 41 52.3 183.1 110.1 37
#> 17.56 21.19 23.88 20.33 12.89 12.21 19.98 21.19 18.02 10.42 9.24 17.56 12.52
#> 154.1 122 185 94 75 31 38 27 119 3 131 46 64
#> 12.63 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 53 186 121 103 44 19 87 46.1 95 162 143 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 74 2.1 135 34 162.1 185.1 9 122.1 38.1 109 147 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 147.1 75.1 94.1 38.2 19.1 196 176 22.1 142.1 3.1 141 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 143.1 151 83 1 116 178 46.2 137 31.1 94.2 17.1 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 182 28 141.1 33 21 138 102 141.2 186.1 200 33.1 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.3 109.1 31.2 44.1 126 28.1 172 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[81]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003401125 0.499839045 0.311859567
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.88614866 0.01470722 0.27885047
#> grade_iii, Cure model
#> 1.31265056
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 32 20.90 1 37 1 0
#> 171 16.57 1 41 0 1
#> 56 12.21 1 60 0 0
#> 136 21.83 1 43 0 1
#> 15 22.68 1 48 0 0
#> 68 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 130 16.47 1 53 0 1
#> 57 14.46 1 45 0 1
#> 100 16.07 1 60 0 0
#> 93 10.33 1 52 0 1
#> 57.1 14.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 130.1 16.47 1 53 0 1
#> 166 19.98 1 48 0 0
#> 183 9.24 1 67 1 0
#> 139 21.49 1 63 1 0
#> 99 21.19 1 38 0 1
#> 45 17.42 1 54 0 1
#> 158 20.14 1 74 1 0
#> 154 12.63 1 20 1 0
#> 100.1 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 56.1 12.21 1 60 0 0
#> 155 13.08 1 26 0 0
#> 85 16.44 1 36 0 0
#> 96 14.54 1 33 0 1
#> 37 12.52 1 57 1 0
#> 166.1 19.98 1 48 0 0
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 188 16.16 1 46 0 1
#> 129.1 23.41 1 53 1 0
#> 55 19.34 1 69 0 1
#> 128 20.35 1 35 0 1
#> 41.1 18.02 1 40 1 0
#> 30 17.43 1 78 0 0
#> 171.1 16.57 1 41 0 1
#> 96.1 14.54 1 33 0 1
#> 169 22.41 1 46 0 0
#> 39 15.59 1 37 0 1
#> 187 9.92 1 39 1 0
#> 100.2 16.07 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 106 16.67 1 49 1 0
#> 93.1 10.33 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 68.2 20.62 1 44 0 0
#> 37.2 12.52 1 57 1 0
#> 183.1 9.24 1 67 1 0
#> 26 15.77 1 49 0 1
#> 133 14.65 1 57 0 0
#> 136.1 21.83 1 43 0 1
#> 70 7.38 1 30 1 0
#> 189.1 10.51 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 56.2 12.21 1 60 0 0
#> 55.1 19.34 1 69 0 1
#> 106.1 16.67 1 49 1 0
#> 69 23.23 1 25 0 1
#> 190.1 20.81 1 42 1 0
#> 70.1 7.38 1 30 1 0
#> 26.1 15.77 1 49 0 1
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 85.1 16.44 1 36 0 0
#> 153 21.33 1 55 1 0
#> 187.1 9.92 1 39 1 0
#> 93.2 10.33 1 52 0 1
#> 78.1 23.88 1 43 0 0
#> 168.1 23.72 1 70 0 0
#> 189.2 10.51 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 179 18.63 1 42 0 0
#> 76 19.22 1 54 0 1
#> 158.1 20.14 1 74 1 0
#> 154.1 12.63 1 20 1 0
#> 60 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 49 12.19 1 48 1 0
#> 100.3 16.07 1 60 0 0
#> 6 15.64 1 39 0 0
#> 157 15.10 1 47 0 0
#> 15.1 22.68 1 48 0 0
#> 63.1 22.77 1 31 1 0
#> 88 18.37 1 47 0 0
#> 86.1 23.81 1 58 0 1
#> 108 18.29 1 39 0 1
#> 168.2 23.72 1 70 0 0
#> 153.1 21.33 1 55 1 0
#> 134 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 123 13.00 1 44 1 0
#> 158.2 20.14 1 74 1 0
#> 70.2 7.38 1 30 1 0
#> 145 10.07 1 65 1 0
#> 187.2 9.92 1 39 1 0
#> 101 9.97 1 10 0 1
#> 30.1 17.43 1 78 0 0
#> 190.2 20.81 1 42 1 0
#> 69.1 23.23 1 25 0 1
#> 111 17.45 1 47 0 1
#> 93.3 10.33 1 52 0 1
#> 90 20.94 1 50 0 1
#> 37.3 12.52 1 57 1 0
#> 175 21.91 1 43 0 0
#> 104 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 71 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 34 24.00 0 36 0 0
#> 112 24.00 0 61 0 0
#> 126 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 104.1 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 146 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 82 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 84 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 27.1 24.00 0 63 1 0
#> 73 24.00 0 NA 0 1
#> 109 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 3.1 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 131 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 152 24.00 0 36 0 1
#> 11 24.00 0 42 0 1
#> 73.1 24.00 0 NA 0 1
#> 137 24.00 0 45 1 0
#> 160 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 94 24.00 0 51 0 1
#> 22 24.00 0 52 1 0
#> 104.2 24.00 0 50 1 0
#> 147.1 24.00 0 76 1 0
#> 143 24.00 0 51 0 0
#> 12.1 24.00 0 63 0 0
#> 173 24.00 0 19 0 1
#> 138.1 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 27.2 24.00 0 63 1 0
#> 173.1 24.00 0 19 0 1
#> 160.1 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 83 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 146.1 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 44 24.00 0 56 0 0
#> 28 24.00 0 67 1 0
#> 44.1 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 103 24.00 0 56 1 0
#> 2.1 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 2.2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 83.1 24.00 0 6 0 0
#> 102.1 24.00 0 49 0 0
#> 44.2 24.00 0 56 0 0
#> 165.1 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 11.1 24.00 0 42 0 1
#> 3.2 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 118.1 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 178 24.00 0 52 1 0
#> 12.2 24.00 0 63 0 0
#> 34.1 24.00 0 36 0 0
#> 44.3 24.00 0 56 0 0
#> 172 24.00 0 41 0 0
#> 174.1 24.00 0 49 1 0
#> 132.2 24.00 0 55 0 0
#> 35 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 148 24.00 0 61 1 0
#> 67 24.00 0 25 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.886 NA NA NA
#> 2 age, Cure model 0.0147 NA NA NA
#> 3 grade_ii, Cure model 0.279 NA NA NA
#> 4 grade_iii, Cure model 1.31 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00340 NA NA NA
#> 2 grade_ii, Survival model 0.500 NA NA NA
#> 3 grade_iii, Survival model 0.312 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88615 0.01471 0.27885 1.31265
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 252.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88614866 0.01470722 0.27885047 1.31265056
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003401125 0.499839045 0.311859567
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.29127211 0.55332578 0.83676213 0.21133196 0.16931190 0.32799756
#> [7] 0.87002294 0.57074717 0.73555744 0.63163096 0.88669748 0.73555744
#> [13] 0.47339928 0.57074717 0.39133363 0.96008265 0.23192737 0.26202078
#> [19] 0.52684848 0.36466614 0.77862667 0.63163096 0.30095504 0.83676213
#> [25] 0.76140898 0.58809412 0.71825692 0.79550925 0.39133363 0.09310338
#> [31] 0.03503947 0.40944576 0.60550028 0.62294969 0.09310338 0.41864224
#> [37] 0.35535469 0.47339928 0.50905533 0.55332578 0.71825692 0.18990129
#> [43] 0.69206144 0.93587544 0.63163096 0.32799756 0.87836593 0.53580062
#> [49] 0.88669748 0.79550925 0.32799756 0.79550925 0.96008265 0.66598862
#> [55] 0.70950709 0.21133196 0.97620434 0.82842167 0.83676213 0.41864224
#> [61] 0.53580062 0.11602144 0.30095504 0.97620434 0.66598862 0.14909536
#> [67] 0.01101206 0.05798369 0.58809412 0.24230866 0.93587544 0.88669748
#> [73] 0.01101206 0.05798369 0.26202078 0.44590388 0.43677009 0.36466614
#> [79] 0.77862667 0.75278823 0.13785829 0.86167114 0.63163096 0.68332414
#> [85] 0.70077624 0.16931190 0.14909536 0.45506264 0.03503947 0.46424873
#> [91] 0.05798369 0.24230866 0.49122419 0.61424803 0.77003800 0.36466614
#> [97] 0.97620434 0.91938200 0.93587544 0.92764046 0.50905533 0.30095504
#> [103] 0.11602144 0.50015280 0.88669748 0.28144101 0.79550925 0.20057763
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 32 171 56 136 15 68 43 130 57 100 93 57.1 41
#> 20.90 16.57 12.21 21.83 22.68 20.62 12.10 16.47 14.46 16.07 10.33 14.46 18.02
#> 130.1 166 183 139 99 45 158 154 100.1 190 56.1 155 85
#> 16.47 19.98 9.24 21.49 21.19 17.42 20.14 12.63 16.07 20.81 12.21 13.08 16.44
#> 96 37 166.1 129 86 105 5 188 129.1 55 128 41.1 30
#> 14.54 12.52 19.98 23.41 23.81 19.75 16.43 16.16 23.41 19.34 20.35 18.02 17.43
#> 171.1 96.1 169 39 187 100.2 68.1 52 106 93.1 37.1 68.2 37.2
#> 16.57 14.54 22.41 15.59 9.92 16.07 20.62 10.42 16.67 10.33 12.52 20.62 12.52
#> 183.1 26 133 136.1 70 42 56.2 55.1 106.1 69 190.1 70.1 26.1
#> 9.24 15.77 14.65 21.83 7.38 12.43 12.21 19.34 16.67 23.23 20.81 7.38 15.77
#> 63 78 168 85.1 153 187.1 93.2 78.1 168.1 99.1 179 76 158.1
#> 22.77 23.88 23.72 16.44 21.33 9.92 10.33 23.88 23.72 21.19 18.63 19.22 20.14
#> 154.1 60 92 49 100.3 6 157 15.1 63.1 88 86.1 108 168.2
#> 12.63 13.15 22.92 12.19 16.07 15.64 15.10 22.68 22.77 18.37 23.81 18.29 23.72
#> 153.1 134 79 123 158.2 70.2 145 187.2 101 30.1 190.2 69.1 111
#> 21.33 17.81 16.23 13.00 20.14 7.38 10.07 9.92 9.97 17.43 20.81 23.23 17.45
#> 93.3 90 37.3 175 104 121 27 47 71 132 34 112 126
#> 10.33 20.94 12.52 21.91 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 200 104.1 141 65 146 198 82 174 138 72 84 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 109 12 3.1 74 2 131 147 152 11 137 160 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 22 104.2 147.1 143 12.1 173 138.1 98.1 27.2 173.1 160.1 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 83 33 109.1 146.1 54 44 28 44.1 165 103 2.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.2 142 83.1 102.1 44.2 165.1 95 118 11.1 3.2 173.2 118.1 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 12.2 34.1 44.3 172 174.1 132.2 35 119 148 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[82]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00849015 0.86017712 0.48433639
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.67309311 0.02767029 0.58381748
#> grade_iii, Cure model
#> 0.88367332
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 124.1 9.73 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 91 5.33 1 61 0 1
#> 199 19.81 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 56 12.21 1 60 0 0
#> 24 23.89 1 38 0 0
#> 49 12.19 1 48 1 0
#> 59 10.16 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 187 9.92 1 39 1 0
#> 93.1 10.33 1 52 0 1
#> 5 16.43 1 51 0 1
#> 123 13.00 1 44 1 0
#> 145 10.07 1 65 1 0
#> 52.1 10.42 1 52 0 1
#> 192 16.44 1 31 1 0
#> 168 23.72 1 70 0 0
#> 124.2 9.73 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 59.1 10.16 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 36 21.19 1 48 0 1
#> 177 12.53 1 75 0 0
#> 169 22.41 1 46 0 0
#> 195 11.76 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 169.1 22.41 1 46 0 0
#> 177.1 12.53 1 75 0 0
#> 187.1 9.92 1 39 1 0
#> 30 17.43 1 78 0 0
#> 5.1 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 167 15.55 1 56 1 0
#> 149 8.37 1 33 1 0
#> 190 20.81 1 42 1 0
#> 157.1 15.10 1 47 0 0
#> 136 21.83 1 43 0 1
#> 90 20.94 1 50 0 1
#> 128 20.35 1 35 0 1
#> 89 11.44 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 111 17.45 1 47 0 1
#> 170 19.54 1 43 0 1
#> 93.2 10.33 1 52 0 1
#> 106 16.67 1 49 1 0
#> 192.1 16.44 1 31 1 0
#> 26 15.77 1 49 0 1
#> 195.1 11.76 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 168.1 23.72 1 70 0 0
#> 197 21.60 1 69 1 0
#> 140 12.68 1 59 1 0
#> 153 21.33 1 55 1 0
#> 50.1 10.02 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 32 20.90 1 37 1 0
#> 164.1 23.60 1 76 0 1
#> 30.1 17.43 1 78 0 0
#> 154 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 29 15.45 1 68 1 0
#> 101 9.97 1 10 0 1
#> 189.1 10.51 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 170.1 19.54 1 43 0 1
#> 10 10.53 1 34 0 0
#> 93.3 10.33 1 52 0 1
#> 110.1 17.56 1 65 0 1
#> 24.1 23.89 1 38 0 0
#> 14 12.89 1 21 0 0
#> 100 16.07 1 60 0 0
#> 107 11.18 1 54 1 0
#> 166 19.98 1 48 0 0
#> 105 19.75 1 60 0 0
#> 194 22.40 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 91.1 5.33 1 61 0 1
#> 194.1 22.40 1 38 0 1
#> 197.1 21.60 1 69 1 0
#> 26.1 15.77 1 49 0 1
#> 128.1 20.35 1 35 0 1
#> 124.3 9.73 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 10.1 10.53 1 34 0 0
#> 194.2 22.40 1 38 0 1
#> 107.1 11.18 1 54 1 0
#> 29.1 15.45 1 68 1 0
#> 136.1 21.83 1 43 0 1
#> 197.2 21.60 1 69 1 0
#> 100.1 16.07 1 60 0 0
#> 158.1 20.14 1 74 1 0
#> 68.1 20.62 1 44 0 0
#> 16 8.71 1 71 0 1
#> 39.1 15.59 1 37 0 1
#> 175 21.91 1 43 0 0
#> 60 13.15 1 38 1 0
#> 90.1 20.94 1 50 0 1
#> 123.1 13.00 1 44 1 0
#> 192.2 16.44 1 31 1 0
#> 25 6.32 1 34 1 0
#> 100.2 16.07 1 60 0 0
#> 42 12.43 1 49 0 1
#> 106.1 16.67 1 49 1 0
#> 82 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 173 24.00 0 19 0 1
#> 144 24.00 0 28 0 1
#> 73 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 74 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 19 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 193.1 24.00 0 45 0 1
#> 196.1 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 98 24.00 0 34 1 0
#> 83 24.00 0 6 0 0
#> 141 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 72 24.00 0 40 0 1
#> 119 24.00 0 17 0 0
#> 151 24.00 0 42 0 0
#> 118 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 143 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 120.1 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 20 24.00 0 46 1 0
#> 151.1 24.00 0 42 0 0
#> 200 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 161 24.00 0 45 0 0
#> 73.1 24.00 0 NA 0 1
#> 104 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 103.1 24.00 0 56 1 0
#> 131.1 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 178 24.00 0 52 1 0
#> 151.2 24.00 0 42 0 0
#> 178.1 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 151.3 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#> 200.1 24.00 0 64 0 0
#> 9 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 161.1 24.00 0 45 0 0
#> 172 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 144.2 24.00 0 28 0 1
#> 94 24.00 0 51 0 1
#> 34 24.00 0 36 0 0
#> 11 24.00 0 42 0 1
#> 141.1 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 87 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 2.2 24.00 0 9 0 0
#> 33.1 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 120.2 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 160.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 119.1 24.00 0 17 0 0
#> 126 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 120.3 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 102.1 24.00 0 49 0 0
#> 191 24.00 0 60 0 1
#> 34.1 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.67 NA NA NA
#> 2 age, Cure model 0.0277 NA NA NA
#> 3 grade_ii, Cure model 0.584 NA NA NA
#> 4 grade_iii, Cure model 0.884 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00849 NA NA NA
#> 2 grade_ii, Survival model 0.860 NA NA NA
#> 3 grade_iii, Survival model 0.484 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.67309 0.02767 0.58382 0.88367
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 239.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.67309311 0.02767029 0.58381748 0.88367332
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00849015 0.86017712 0.48433639
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.41088009 0.85966264 0.20746212 0.98166774 0.87870348 0.34818843
#> [7] 0.79274325 0.00422316 0.80246002 0.44277582 0.93527872 0.87870348
#> [13] 0.55634717 0.71552906 0.91630226 0.85966264 0.52688774 0.01679921
#> [19] 0.68579702 0.30607928 0.23076103 0.76383759 0.07210872 0.03677859
#> [25] 0.07210872 0.76383759 0.93527872 0.47423800 0.55634717 0.51639067
#> [31] 0.43222807 0.65614600 0.96319285 0.29552454 0.68579702 0.14817039
#> [37] 0.26292356 0.32727298 0.23076103 0.46368449 0.38998860 0.87870348
#> [43] 0.49556481 0.52688774 0.61606015 0.05884692 0.01679921 0.17333960
#> [49] 0.74458495 0.21926053 0.83107353 0.28471717 0.03677859 0.47423800
#> [55] 0.75427235 0.57612728 0.66614347 0.92581436 0.63616163 0.38998860
#> [61] 0.84060333 0.87870348 0.44277582 0.00422316 0.73484275 0.58608676
#> [67] 0.81210989 0.36878149 0.37932589 0.09918260 0.23076103 0.98166774
#> [73] 0.09918260 0.17333960 0.61606015 0.32727298 0.42152734 0.84060333
#> [79] 0.09918260 0.81210989 0.66614347 0.14817039 0.17333960 0.58608676
#> [85] 0.34818843 0.30607928 0.95385090 0.63616163 0.13470331 0.70563769
#> [91] 0.26292356 0.71552906 0.52688774 0.97246412 0.58608676 0.78307379
#> [97] 0.49556481 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 8 52 139 91 93 158 56 24 49 110 187 93.1 5
#> 18.43 10.42 21.49 5.33 10.33 20.14 12.21 23.89 12.19 17.56 9.92 10.33 16.43
#> 123 145 52.1 192 168 157 68 36 177 169 164 169.1 177.1
#> 13.00 10.07 10.42 16.44 23.72 15.10 20.62 21.19 12.53 22.41 23.60 22.41 12.53
#> 187.1 30 5.1 181 134 167 149 190 157.1 136 90 128 99
#> 9.92 17.43 16.43 16.46 17.81 15.55 8.37 20.81 15.10 21.83 20.94 20.35 21.19
#> 111 170 93.2 106 192.1 26 15 168.1 197 140 153 159 32
#> 17.45 19.54 10.33 16.67 16.44 15.77 22.68 23.72 21.60 12.68 21.33 10.55 20.90
#> 164.1 30.1 154 188 29 101 39 170.1 10 93.3 110.1 24.1 14
#> 23.60 17.43 12.63 16.16 15.45 9.97 15.59 19.54 10.53 10.33 17.56 23.89 12.89
#> 100 107 166 105 194 99.1 91.1 194.1 197.1 26.1 128.1 51 10.1
#> 16.07 11.18 19.98 19.75 22.40 21.19 5.33 22.40 21.60 15.77 20.35 18.23 10.53
#> 194.2 107.1 29.1 136.1 197.2 100.1 158.1 68.1 16 39.1 175 60 90.1
#> 22.40 11.18 15.45 21.83 21.60 16.07 20.14 20.62 8.71 15.59 21.91 13.15 20.94
#> 123.1 192.2 25 100.2 42 106.1 82 165 142 193 103 173 144
#> 13.00 16.44 6.32 16.07 12.43 16.67 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 74 27 137 131 46 17 2 19 196 193.1 196.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 98 83 141 28 72 119 151 118 163 2.1 143 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 152 20 151.1 200 84 161 104 144.1 103.1 131.1 160 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 151.2 178.1 176 162 21 151.3 62 200.1 9 22 161.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 144.2 94 34 11 141.1 20.1 87 156 2.2 33.1 48 120.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 31 160.1 109 119.1 126 47 120.3 186 185 102.1 191 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[83]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01093173 0.58833944 0.69667130
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.458908393 0.009878378 -0.346078479
#> grade_iii, Cure model
#> 0.753061122
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 8 18.43 1 32 0 0
#> 89 11.44 1 NA 0 0
#> 90.1 20.94 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 110 17.56 1 65 0 1
#> 5 16.43 1 51 0 1
#> 179 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 66 22.13 1 53 0 0
#> 56 12.21 1 60 0 0
#> 108 18.29 1 39 0 1
#> 25 6.32 1 34 1 0
#> 99 21.19 1 38 0 1
#> 114 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 13 14.34 1 54 0 1
#> 51 18.23 1 83 0 1
#> 42 12.43 1 49 0 1
#> 111 17.45 1 47 0 1
#> 175 21.91 1 43 0 0
#> 164 23.60 1 76 0 1
#> 129 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 187 9.92 1 39 1 0
#> 88 18.37 1 47 0 0
#> 88.1 18.37 1 47 0 0
#> 85 16.44 1 36 0 0
#> 5.1 16.43 1 51 0 1
#> 106 16.67 1 49 1 0
#> 168 23.72 1 70 0 0
#> 150 20.33 1 48 0 0
#> 32 20.90 1 37 1 0
#> 43 12.10 1 61 0 1
#> 39 15.59 1 37 0 1
#> 4 17.64 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 129.1 23.41 1 53 1 0
#> 4.1 17.64 1 NA 0 1
#> 195 11.76 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 158 20.14 1 74 1 0
#> 24 23.89 1 38 0 0
#> 57 14.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 60 13.15 1 38 1 0
#> 91 5.33 1 61 0 1
#> 101 9.97 1 10 0 1
#> 51.1 18.23 1 83 0 1
#> 50 10.02 1 NA 1 0
#> 168.1 23.72 1 70 0 0
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 149 8.37 1 33 1 0
#> 188 16.16 1 46 0 1
#> 166 19.98 1 48 0 0
#> 153 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 139 21.49 1 63 1 0
#> 153.1 21.33 1 55 1 0
#> 97.1 19.14 1 65 0 1
#> 36 21.19 1 48 0 1
#> 78 23.88 1 43 0 0
#> 168.2 23.72 1 70 0 0
#> 6 15.64 1 39 0 0
#> 78.1 23.88 1 43 0 0
#> 30 17.43 1 78 0 0
#> 140 12.68 1 59 1 0
#> 60.1 13.15 1 38 1 0
#> 187.1 9.92 1 39 1 0
#> 179.1 18.63 1 42 0 0
#> 127 3.53 1 62 0 1
#> 25.1 6.32 1 34 1 0
#> 63 22.77 1 31 1 0
#> 42.1 12.43 1 49 0 1
#> 10 10.53 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 15 22.68 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 86 23.81 1 58 0 1
#> 170 19.54 1 43 0 1
#> 96 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 68 20.62 1 44 0 0
#> 123 13.00 1 44 1 0
#> 181 16.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 195.1 11.76 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 77 7.27 1 67 0 1
#> 145 10.07 1 65 1 0
#> 29 15.45 1 68 1 0
#> 129.2 23.41 1 53 1 0
#> 40 18.00 1 28 1 0
#> 91.1 5.33 1 61 0 1
#> 6.1 15.64 1 39 0 0
#> 45.1 17.42 1 54 0 1
#> 36.1 21.19 1 48 0 1
#> 189 10.51 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 130 16.47 1 53 0 1
#> 49 12.19 1 48 1 0
#> 114.1 13.68 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 195.2 11.76 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 184.1 17.77 1 38 0 0
#> 43.1 12.10 1 61 0 1
#> 124 9.73 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 200 24.00 0 64 0 0
#> 146 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 44 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 80 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 11 24.00 0 42 0 1
#> 119 24.00 0 17 0 0
#> 126 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 1 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 104 24.00 0 50 1 0
#> 178.1 24.00 0 52 1 0
#> 104.1 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 7 24.00 0 37 1 0
#> 115 24.00 0 NA 1 0
#> 22 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 103 24.00 0 56 1 0
#> 94.1 24.00 0 51 0 1
#> 163.1 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 48.1 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 120 24.00 0 68 0 1
#> 147.1 24.00 0 76 1 0
#> 17 24.00 0 38 0 1
#> 103.1 24.00 0 56 1 0
#> 48.2 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 156 24.00 0 50 1 0
#> 1.1 24.00 0 23 1 0
#> 2 24.00 0 9 0 0
#> 191 24.00 0 60 0 1
#> 135 24.00 0 58 1 0
#> 161 24.00 0 45 0 0
#> 17.1 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 83 24.00 0 6 0 0
#> 17.2 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 104.2 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 103.2 24.00 0 56 1 0
#> 131 24.00 0 66 0 0
#> 1.2 24.00 0 23 1 0
#> 162 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 161.1 24.00 0 45 0 0
#> 104.3 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 147.2 24.00 0 76 1 0
#> 3 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 75 24.00 0 21 1 0
#> 146.1 24.00 0 63 1 0
#> 191.2 24.00 0 60 0 1
#> 138.1 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 104.4 24.00 0 50 1 0
#> 38.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 176.1 24.00 0 43 0 1
#> 138.2 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 198.1 24.00 0 66 0 1
#> 172.2 24.00 0 41 0 0
#> 74.1 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 135.1 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.459 NA NA NA
#> 2 age, Cure model 0.00988 NA NA NA
#> 3 grade_ii, Cure model -0.346 NA NA NA
#> 4 grade_iii, Cure model 0.753 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0109 NA NA NA
#> 2 grade_ii, Survival model 0.588 NA NA NA
#> 3 grade_iii, Survival model 0.697 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.458908 0.009878 -0.346078 0.753061
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 246.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.458908393 0.009878378 -0.346078479 0.753061122
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01093173 0.58833944 0.69667130
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.215155749 0.364792734 0.215155749 0.780030719 0.460810219 0.578765314
#> [7] 0.344179449 0.439312308 0.126582228 0.811531409 0.396607314 0.948271283
#> [13] 0.187021828 0.610458288 0.695781261 0.407298076 0.790610517 0.482445367
#> [19] 0.136423084 0.050807598 0.061479957 0.769455824 0.896076557 0.375338485
#> [25] 0.375338485 0.557557480 0.578765314 0.525340995 0.025574559 0.253377835
#> [31] 0.234074234 0.832712184 0.642597607 0.864350304 0.061479957 0.758961626
#> [37] 0.263257484 0.001409612 0.685170667 0.557557480 0.706373731 0.968949800
#> [43] 0.885563344 0.407298076 0.025574559 0.916894259 0.303499431 0.927372015
#> [49] 0.599857852 0.273211118 0.167047723 0.324011099 0.156760614 0.167047723
#> [55] 0.324011099 0.187021828 0.006412824 0.025574559 0.621148015 0.006412824
#> [61] 0.493151747 0.748402122 0.706373731 0.896076557 0.344179449 0.989614978
#> [67] 0.948271283 0.088357387 0.790610517 0.853733372 0.098105732 0.642597607
#> [73] 0.018272951 0.293344158 0.674522610 0.146537780 0.243653029 0.737850817
#> [79] 0.546859443 0.108266817 0.503993169 0.108266817 0.937819604 0.874949427
#> [85] 0.663807026 0.061479957 0.428608907 0.968949800 0.621148015 0.503993169
#> [91] 0.187021828 0.273211118 0.536113650 0.822126276 0.471691108 0.727282389
#> [97] 0.439312308 0.832712184 0.313774058 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 90 8 90.1 37 110 5 179 184 66 56 108 25 99
#> 20.94 18.43 20.94 12.52 17.56 16.43 18.63 17.77 22.13 12.21 18.29 6.32 21.19
#> 100 13 51 42 111 175 164 129 177 187 88 88.1 85
#> 16.07 14.34 18.23 12.43 17.45 21.91 23.60 23.41 12.53 9.92 18.37 18.37 16.44
#> 5.1 106 168 150 32 43 39 93 129.1 154 158 24 57
#> 16.43 16.67 23.72 20.33 20.90 12.10 15.59 10.33 23.41 12.63 20.14 23.89 14.46
#> 192 60 91 101 51.1 168.1 16 58 149 188 166 153 97
#> 16.44 13.15 5.33 9.97 18.23 23.72 8.71 19.34 8.37 16.16 19.98 21.33 19.14
#> 139 153.1 97.1 36 78 168.2 6 78.1 30 140 60.1 187.1 179.1
#> 21.49 21.33 19.14 21.19 23.88 23.72 15.64 23.88 17.43 12.68 13.15 9.92 18.63
#> 127 25.1 63 42.1 10 15 39.1 86 170 96 197 68 123
#> 3.53 6.32 22.77 12.43 10.53 22.68 15.59 23.81 19.54 14.54 21.60 20.62 13.00
#> 181 194 45 194.1 77 145 29 129.2 40 91.1 6.1 45.1 36.1
#> 16.46 22.40 17.42 22.40 7.27 10.07 15.45 23.41 18.00 5.33 15.64 17.42 21.19
#> 166.1 130 49 117 155 184.1 43.1 76 200 146 48 64 44
#> 19.98 16.47 12.19 17.46 13.08 17.77 12.10 19.22 24.00 24.00 24.00 24.00 24.00
#> 196 151 80 54 11 119 126 98 1 47 46 163 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 178 104 178.1 104.1 74 7 22 94 103 94.1 163.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 143 147 120 147.1 17 103.1 48.2 7.1 12 156 1.1 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 135 161 17.1 116 83 17.2 64.1 38 62 172 173 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 34.1 103.2 131 1.2 162 191.1 161.1 104.3 27 147.2 3 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 146.1 191.2 138.1 176 198 104.4 38.1 172.1 176.1 138.2 185 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.2 74.1 33 135.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[84]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005943019 0.398819462 0.124174444
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.577156272 0.004585949 0.506746406
#> grade_iii, Cure model
#> 1.489183850
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 180 14.82 1 37 0 0
#> 124 9.73 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 50 10.02 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 169 22.41 1 46 0 0
#> 117 17.46 1 26 0 1
#> 184 17.77 1 38 0 0
#> 66 22.13 1 53 0 0
#> 101 9.97 1 10 0 1
#> 26 15.77 1 49 0 1
#> 125 15.65 1 67 1 0
#> 187 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 36 21.19 1 48 0 1
#> 55 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 108.1 18.29 1 39 0 1
#> 40 18.00 1 28 1 0
#> 15 22.68 1 48 0 0
#> 40.1 18.00 1 28 1 0
#> 63 22.77 1 31 1 0
#> 55.1 19.34 1 69 0 1
#> 88 18.37 1 47 0 0
#> 14 12.89 1 21 0 0
#> 175 21.91 1 43 0 0
#> 101.1 9.97 1 10 0 1
#> 188 16.16 1 46 0 1
#> 171 16.57 1 41 0 1
#> 183 9.24 1 67 1 0
#> 88.1 18.37 1 47 0 0
#> 157 15.10 1 47 0 0
#> 69 23.23 1 25 0 1
#> 140 12.68 1 59 1 0
#> 43 12.10 1 61 0 1
#> 57 14.46 1 45 0 1
#> 81.1 14.06 1 34 0 0
#> 155 13.08 1 26 0 0
#> 57.1 14.46 1 45 0 1
#> 125.1 15.65 1 67 1 0
#> 157.1 15.10 1 47 0 0
#> 55.2 19.34 1 69 0 1
#> 70 7.38 1 30 1 0
#> 189 10.51 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 111 17.45 1 47 0 1
#> 117.1 17.46 1 26 0 1
#> 77 7.27 1 67 0 1
#> 97 19.14 1 65 0 1
#> 177 12.53 1 75 0 0
#> 197 21.60 1 69 1 0
#> 29 15.45 1 68 1 0
#> 79 16.23 1 54 1 0
#> 157.2 15.10 1 47 0 0
#> 8 18.43 1 32 0 0
#> 139 21.49 1 63 1 0
#> 145 10.07 1 65 1 0
#> 90 20.94 1 50 0 1
#> 90.1 20.94 1 50 0 1
#> 96 14.54 1 33 0 1
#> 16 8.71 1 71 0 1
#> 190 20.81 1 42 1 0
#> 149 8.37 1 33 1 0
#> 25 6.32 1 34 1 0
#> 10 10.53 1 34 0 0
#> 111.1 17.45 1 47 0 1
#> 158 20.14 1 74 1 0
#> 39 15.59 1 37 0 1
#> 150 20.33 1 48 0 0
#> 157.3 15.10 1 47 0 0
#> 66.1 22.13 1 53 0 0
#> 157.4 15.10 1 47 0 0
#> 18 15.21 1 49 1 0
#> 139.1 21.49 1 63 1 0
#> 192 16.44 1 31 1 0
#> 24 23.89 1 38 0 0
#> 136 21.83 1 43 0 1
#> 4.1 17.64 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 85 16.44 1 36 0 0
#> 69.1 23.23 1 25 0 1
#> 10.1 10.53 1 34 0 0
#> 92 22.92 1 47 0 1
#> 187.1 9.92 1 39 1 0
#> 158.1 20.14 1 74 1 0
#> 97.1 19.14 1 65 0 1
#> 117.2 17.46 1 26 0 1
#> 134 17.81 1 47 1 0
#> 195 11.76 1 NA 1 0
#> 10.2 10.53 1 34 0 0
#> 25.1 6.32 1 34 1 0
#> 184.1 17.77 1 38 0 0
#> 149.1 8.37 1 33 1 0
#> 171.1 16.57 1 41 0 1
#> 89 11.44 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 127 3.53 1 62 0 1
#> 127.1 3.53 1 62 0 1
#> 194 22.40 1 38 0 1
#> 139.2 21.49 1 63 1 0
#> 45 17.42 1 54 0 1
#> 40.2 18.00 1 28 1 0
#> 59.1 10.16 1 NA 1 0
#> 128.1 20.35 1 35 0 1
#> 197.1 21.60 1 69 1 0
#> 100 16.07 1 60 0 0
#> 78 23.88 1 43 0 0
#> 124.1 9.73 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 95 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 21 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 135 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#> 156.1 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 160 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 151 24.00 0 42 0 0
#> 73 24.00 0 NA 0 1
#> 109 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 7 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 73.1 24.00 0 NA 0 1
#> 160.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 17.1 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 172 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 34.1 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 87 24.00 0 27 0 0
#> 102 24.00 0 49 0 0
#> 47 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#> 27.1 24.00 0 63 1 0
#> 34.2 24.00 0 36 0 0
#> 162 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 193 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 38 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 156.2 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 3 24.00 0 31 1 0
#> 34.3 24.00 0 36 0 0
#> 102.1 24.00 0 49 0 0
#> 12.1 24.00 0 63 0 0
#> 34.4 24.00 0 36 0 0
#> 46 24.00 0 71 0 0
#> 87.2 24.00 0 27 0 0
#> 120.1 24.00 0 68 0 1
#> 64.1 24.00 0 43 0 0
#> 200 24.00 0 64 0 0
#> 126 24.00 0 48 0 0
#> 48.1 24.00 0 31 1 0
#> 142.1 24.00 0 53 0 0
#> 135.1 24.00 0 58 1 0
#> 21.1 24.00 0 47 0 0
#> 71.1 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 120.2 24.00 0 68 0 1
#> 35 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 94.1 24.00 0 51 0 1
#> 3.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 151.2 24.00 0 42 0 0
#> 71.2 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 54 24.00 0 53 1 0
#> 200.1 24.00 0 64 0 0
#> 47.1 24.00 0 38 0 1
#> 83.1 24.00 0 6 0 0
#> 35.1 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.577 NA NA NA
#> 2 age, Cure model 0.00459 NA NA NA
#> 3 grade_ii, Cure model 0.507 NA NA NA
#> 4 grade_iii, Cure model 1.49 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00594 NA NA NA
#> 2 grade_ii, Survival model 0.399 NA NA NA
#> 3 grade_iii, Survival model 0.124 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.577156 0.004586 0.506746 1.489184
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 242.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.577156272 0.004585949 0.506746406 1.489183850
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005943019 0.398819462 0.124174444
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.679000562 0.286638705 0.346045729 0.474450386 0.061431666 0.425052408
#> [7] 0.405238941 0.078356163 0.849657336 0.566188090 0.576523302 0.871221561
#> [13] 0.731679443 0.157190537 0.258370807 0.248852068 0.346045729 0.366165071
#> [19] 0.053287581 0.366165071 0.045442756 0.258370807 0.326045307 0.763594445
#> [25] 0.095412720 0.849657336 0.545632554 0.494828997 0.892689215 0.326045307
#> [31] 0.628034673 0.023104102 0.774315423 0.795795586 0.710579733 0.731679443
#> [37] 0.752891100 0.710579733 0.576523302 0.628034673 0.258370807 0.935743816
#> [43] 0.014760935 0.454485098 0.425052408 0.946486882 0.296448888 0.785029082
#> [49] 0.113796006 0.607356193 0.535409906 0.628034673 0.316038984 0.131565271
#> [55] 0.838787373 0.166322058 0.166322058 0.699992675 0.903488280 0.184391847
#> [61] 0.914320692 0.957259254 0.806593072 0.454485098 0.221018382 0.597008062
#> [67] 0.211671880 0.628034673 0.078356163 0.628034673 0.617705262 0.131565271
#> [73] 0.515128737 0.002231382 0.104554395 0.239377982 0.515128737 0.023104102
#> [79] 0.806593072 0.037264618 0.871221561 0.221018382 0.296448888 0.425052408
#> [85] 0.395307543 0.806593072 0.957259254 0.405238941 0.914320692 0.494828997
#> [91] 0.193585402 0.978579045 0.978579045 0.069843794 0.131565271 0.484620557
#> [97] 0.366165071 0.193585402 0.113796006 0.555881823 0.007814567 0.679000562
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 180 76 108 30 169 117 184 66 101 26 125 187 81
#> 14.82 19.22 18.29 17.43 22.41 17.46 17.77 22.13 9.97 15.77 15.65 9.92 14.06
#> 36 55 170 108.1 40 15 40.1 63 55.1 88 14 175 101.1
#> 21.19 19.34 19.54 18.29 18.00 22.68 18.00 22.77 19.34 18.37 12.89 21.91 9.97
#> 188 171 183 88.1 157 69 140 43 57 81.1 155 57.1 125.1
#> 16.16 16.57 9.24 18.37 15.10 23.23 12.68 12.10 14.46 14.06 13.08 14.46 15.65
#> 157.1 55.2 70 168 111 117.1 77 97 177 197 29 79 157.2
#> 15.10 19.34 7.38 23.72 17.45 17.46 7.27 19.14 12.53 21.60 15.45 16.23 15.10
#> 8 139 145 90 90.1 96 16 190 149 25 10 111.1 158
#> 18.43 21.49 10.07 20.94 20.94 14.54 8.71 20.81 8.37 6.32 10.53 17.45 20.14
#> 39 150 157.3 66.1 157.4 18 139.1 192 24 136 105 85 69.1
#> 15.59 20.33 15.10 22.13 15.10 15.21 21.49 16.44 23.89 21.83 19.75 16.44 23.23
#> 10.1 92 187.1 158.1 97.1 117.2 134 10.2 25.1 184.1 149.1 171.1 128
#> 10.53 22.92 9.92 20.14 19.14 17.46 17.81 10.53 6.32 17.77 8.37 16.57 20.35
#> 127 127.1 194 139.2 45 40.2 128.1 197.1 100 78 180.1 95 147
#> 3.53 3.53 22.40 21.49 17.42 18.00 20.35 21.60 16.07 23.88 14.82 24.00 24.00
#> 21 12 135 156 156.1 17 67 31 1 160 142 28 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 151 109 34 7 27 62 64 160.1 71 17.1 174 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 34.1 120 196 87 102 47 87.1 27.1 34.2 162 20 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 38 2 165 48 156.2 22 3 34.3 102.1 12.1 34.4 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.2 120.1 64.1 200 126 48.1 142.1 135.1 21.1 71.1 67.1 120.2 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 38.1 151.1 94.1 3.1 80 185 151.2 71.2 80.1 83 54 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 83.1 35.1 131 118 44
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[85]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004849633 0.533163428 0.502377390
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.586249338 0.009734854 0.525264049
#> grade_iii, Cure model
#> 0.465180092
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 57 14.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 110 17.56 1 65 0 1
#> 190 20.81 1 42 1 0
#> 52 10.42 1 52 0 1
#> 110.1 17.56 1 65 0 1
#> 192 16.44 1 31 1 0
#> 43 12.10 1 61 0 1
#> 155 13.08 1 26 0 0
#> 139 21.49 1 63 1 0
#> 51 18.23 1 83 0 1
#> 58 19.34 1 39 0 0
#> 125 15.65 1 67 1 0
#> 105 19.75 1 60 0 0
#> 24 23.89 1 38 0 0
#> 140 12.68 1 59 1 0
#> 45 17.42 1 54 0 1
#> 36 21.19 1 48 0 1
#> 180 14.82 1 37 0 0
#> 139.1 21.49 1 63 1 0
#> 177 12.53 1 75 0 0
#> 69 23.23 1 25 0 1
#> 155.1 13.08 1 26 0 0
#> 111 17.45 1 47 0 1
#> 129 23.41 1 53 1 0
#> 39 15.59 1 37 0 1
#> 189 10.51 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 81 14.06 1 34 0 0
#> 24.1 23.89 1 38 0 0
#> 32 20.90 1 37 1 0
#> 81.1 14.06 1 34 0 0
#> 168 23.72 1 70 0 0
#> 59 10.16 1 NA 1 0
#> 43.1 12.10 1 61 0 1
#> 24.2 23.89 1 38 0 0
#> 181 16.46 1 45 0 1
#> 42 12.43 1 49 0 1
#> 106 16.67 1 49 1 0
#> 8 18.43 1 32 0 0
#> 177.1 12.53 1 75 0 0
#> 157 15.10 1 47 0 0
#> 164 23.60 1 76 0 1
#> 86 23.81 1 58 0 1
#> 78 23.88 1 43 0 0
#> 56 12.21 1 60 0 0
#> 136 21.83 1 43 0 1
#> 40 18.00 1 28 1 0
#> 105.1 19.75 1 60 0 0
#> 140.1 12.68 1 59 1 0
#> 23 16.92 1 61 0 0
#> 197 21.60 1 69 1 0
#> 93 10.33 1 52 0 1
#> 88 18.37 1 47 0 0
#> 4 17.64 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 108 18.29 1 39 0 1
#> 66.1 22.13 1 53 0 0
#> 16 8.71 1 71 0 1
#> 8.1 18.43 1 32 0 0
#> 39.1 15.59 1 37 0 1
#> 61 10.12 1 36 0 1
#> 180.1 14.82 1 37 0 0
#> 164.2 23.60 1 76 0 1
#> 70 7.38 1 30 1 0
#> 41 18.02 1 40 1 0
#> 108.1 18.29 1 39 0 1
#> 134 17.81 1 47 1 0
#> 4.1 17.64 1 NA 0 1
#> 110.2 17.56 1 65 0 1
#> 106.1 16.67 1 49 1 0
#> 52.1 10.42 1 52 0 1
#> 14 12.89 1 21 0 0
#> 125.1 15.65 1 67 1 0
#> 192.1 16.44 1 31 1 0
#> 96 14.54 1 33 0 1
#> 183 9.24 1 67 1 0
#> 188 16.16 1 46 0 1
#> 184 17.77 1 38 0 0
#> 133 14.65 1 57 0 0
#> 159 10.55 1 50 0 1
#> 133.1 14.65 1 57 0 0
#> 91 5.33 1 61 0 1
#> 188.1 16.16 1 46 0 1
#> 140.2 12.68 1 59 1 0
#> 92 22.92 1 47 0 1
#> 59.1 10.16 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 24.3 23.89 1 38 0 0
#> 86.1 23.81 1 58 0 1
#> 16.1 8.71 1 71 0 1
#> 93.1 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 130 16.47 1 53 0 1
#> 192.2 16.44 1 31 1 0
#> 85 16.44 1 36 0 0
#> 113 22.86 1 34 0 0
#> 150 20.33 1 48 0 0
#> 158 20.14 1 74 1 0
#> 59.2 10.16 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 129.1 23.41 1 53 1 0
#> 41.1 18.02 1 40 1 0
#> 192.3 16.44 1 31 1 0
#> 41.2 18.02 1 40 1 0
#> 180.2 14.82 1 37 0 0
#> 36.1 21.19 1 48 0 1
#> 26 15.77 1 49 0 1
#> 195 11.76 1 NA 1 0
#> 34 24.00 0 36 0 0
#> 131 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 22 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 64 24.00 0 43 0 0
#> 1 24.00 0 23 1 0
#> 198 24.00 0 66 0 1
#> 19 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 191 24.00 0 60 0 1
#> 22.1 24.00 0 52 1 0
#> 191.1 24.00 0 60 0 1
#> 82 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 33 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 142 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 64.1 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 191.2 24.00 0 60 0 1
#> 163 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 19.1 24.00 0 57 0 1
#> 198.1 24.00 0 66 0 1
#> 132.1 24.00 0 55 0 0
#> 172.1 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 20 24.00 0 46 1 0
#> 132.2 24.00 0 55 0 0
#> 87 24.00 0 27 0 0
#> 182 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 172.2 24.00 0 41 0 0
#> 142.1 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 165.1 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 143 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 141 24.00 0 44 1 0
#> 143.1 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 95 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#> 64.2 24.00 0 43 0 0
#> 122 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 11.1 24.00 0 42 0 1
#> 193.1 24.00 0 45 0 1
#> 118 24.00 0 44 1 0
#> 198.2 24.00 0 66 0 1
#> 198.3 24.00 0 66 0 1
#> 116.1 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 143.2 24.00 0 51 0 0
#> 116.2 24.00 0 58 0 1
#> 33.2 24.00 0 53 0 0
#> 17.1 24.00 0 38 0 1
#> 21.2 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 84 24.00 0 39 0 1
#> 152.1 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 104 24.00 0 50 1 0
#> 9.1 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 173 24.00 0 19 0 1
#> 87.1 24.00 0 27 0 0
#> 48.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.586 NA NA NA
#> 2 age, Cure model 0.00973 NA NA NA
#> 3 grade_ii, Cure model 0.525 NA NA NA
#> 4 grade_iii, Cure model 0.465 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00485 NA NA NA
#> 2 grade_ii, Survival model 0.533 NA NA NA
#> 3 grade_iii, Survival model 0.502 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.586249 0.009735 0.525264 0.465180
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 259.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.586249338 0.009734854 0.525264049 0.465180092
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004849633 0.533163428 0.502377390
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.75931542 0.75056429 0.35330691 0.49139931 0.30305401 0.90665162
#> [7] 0.49139931 0.58463399 0.88074594 0.79415991 0.25187611 0.42384159
#> [13] 0.36339417 0.65471963 0.33322745 0.01537862 0.82027720 0.52880175
#> [19] 0.27262113 0.69821624 0.25187611 0.84600018 0.15480311 0.79415991
#> [25] 0.51936265 0.13335630 0.67219012 0.19752990 0.76803922 0.01537862
#> [31] 0.29288985 0.76803922 0.08809971 0.88074594 0.01537862 0.57540279
#> [37] 0.86334469 0.54763098 0.37352994 0.84600018 0.68948926 0.10094796
#> [43] 0.06516793 0.05117943 0.87203436 0.23011299 0.46253849 0.33322745
#> [49] 0.82027720 0.53819528 0.24104844 0.92377003 0.39368173 0.10094796
#> [55] 0.40394422 0.19752990 0.96631367 0.37352994 0.67219012 0.94079875
#> [61] 0.69821624 0.10094796 0.98316297 0.43388482 0.40394422 0.47219467
#> [67] 0.49139931 0.54763098 0.90665162 0.81153403 0.65471963 0.58463399
#> [73] 0.74177949 0.95782652 0.62822010 0.48178089 0.72422961 0.89800500
#> [79] 0.72422961 0.99158968 0.62822010 0.82027720 0.16556775 0.18676158
#> [85] 0.01537862 0.06516793 0.96631367 0.92377003 0.78544752 0.94932193
#> [91] 0.56612267 0.58463399 0.58463399 0.17611612 0.31308690 0.32318703
#> [97] 0.21899724 0.13335630 0.43388482 0.58463399 0.43388482 0.69821624
#> [103] 0.27262113 0.64587030 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 13 57 170 110 190 52 110.1 192 43 155 139 51 58
#> 14.34 14.46 19.54 17.56 20.81 10.42 17.56 16.44 12.10 13.08 21.49 18.23 19.34
#> 125 105 24 140 45 36 180 139.1 177 69 155.1 111 129
#> 15.65 19.75 23.89 12.68 17.42 21.19 14.82 21.49 12.53 23.23 13.08 17.45 23.41
#> 39 66 81 24.1 32 81.1 168 43.1 24.2 181 42 106 8
#> 15.59 22.13 14.06 23.89 20.90 14.06 23.72 12.10 23.89 16.46 12.43 16.67 18.43
#> 177.1 157 164 86 78 56 136 40 105.1 140.1 23 197 93
#> 12.53 15.10 23.60 23.81 23.88 12.21 21.83 18.00 19.75 12.68 16.92 21.60 10.33
#> 88 164.1 108 66.1 16 8.1 39.1 61 180.1 164.2 70 41 108.1
#> 18.37 23.60 18.29 22.13 8.71 18.43 15.59 10.12 14.82 23.60 7.38 18.02 18.29
#> 134 110.2 106.1 52.1 14 125.1 192.1 96 183 188 184 133 159
#> 17.81 17.56 16.67 10.42 12.89 15.65 16.44 14.54 9.24 16.16 17.77 14.65 10.55
#> 133.1 91 188.1 140.2 92 169 24.3 86.1 16.1 93.1 60 145 130
#> 14.65 5.33 16.16 12.68 22.92 22.41 23.89 23.81 8.71 10.33 13.15 10.07 16.47
#> 192.2 85 113 150 158 175 129.1 41.1 192.3 41.2 180.2 36.1 26
#> 16.44 16.44 22.86 20.33 20.14 21.91 23.41 18.02 16.44 18.02 14.82 21.19 15.77
#> 34 131 98 22 38 53 64 1 198 19 44 191 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 82 116 33 193 71 152 28 142 132 64.1 172 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.2 163 48 176 19.1 198.1 132.1 172.1 112 161 20 132.2 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 165 21.1 120 12 103 162 172.2 142.1 17 11 165.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 33.1 126 3 2 141 143.1 176.1 95 47 64.2 122 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 193.1 118 198.2 198.3 116.1 143.2 116.2 33.2 17.1 21.2 151 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 9 178 104 9.1 112.1 173 87.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[86]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01098683 0.79125168 0.70593887
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.139230619 0.002291625 0.120851229
#> grade_iii, Cure model
#> 0.749070435
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 16 8.71 1 71 0 1
#> 190 20.81 1 42 1 0
#> 139 21.49 1 63 1 0
#> 166 19.98 1 48 0 0
#> 117 17.46 1 26 0 1
#> 41 18.02 1 40 1 0
#> 41.1 18.02 1 40 1 0
#> 113 22.86 1 34 0 0
#> 60 13.15 1 38 1 0
#> 170 19.54 1 43 0 1
#> 40 18.00 1 28 1 0
#> 41.2 18.02 1 40 1 0
#> 168 23.72 1 70 0 0
#> 36 21.19 1 48 0 1
#> 177 12.53 1 75 0 0
#> 183 9.24 1 67 1 0
#> 129 23.41 1 53 1 0
#> 8 18.43 1 32 0 0
#> 155 13.08 1 26 0 0
#> 171 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 49 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 157 15.10 1 47 0 0
#> 97 19.14 1 65 0 1
#> 188 16.16 1 46 0 1
#> 111 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 4 17.64 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 130 16.47 1 53 0 1
#> 128 20.35 1 35 0 1
#> 41.3 18.02 1 40 1 0
#> 8.1 18.43 1 32 0 0
#> 189 10.51 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 61 10.12 1 36 0 1
#> 100 16.07 1 60 0 0
#> 194.1 22.40 1 38 0 1
#> 157.1 15.10 1 47 0 0
#> 127 3.53 1 62 0 1
#> 45 17.42 1 54 0 1
#> 169 22.41 1 46 0 0
#> 194.2 22.40 1 38 0 1
#> 97.1 19.14 1 65 0 1
#> 66 22.13 1 53 0 0
#> 127.1 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 188.1 16.16 1 46 0 1
#> 136 21.83 1 43 0 1
#> 81 14.06 1 34 0 0
#> 175 21.91 1 43 0 0
#> 63 22.77 1 31 1 0
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 45.1 17.42 1 54 0 1
#> 60.1 13.15 1 38 1 0
#> 29 15.45 1 68 1 0
#> 25 6.32 1 34 1 0
#> 90 20.94 1 50 0 1
#> 24 23.89 1 38 0 0
#> 157.2 15.10 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 127.2 3.53 1 62 0 1
#> 61.1 10.12 1 36 0 1
#> 29.1 15.45 1 68 1 0
#> 139.1 21.49 1 63 1 0
#> 153.1 21.33 1 55 1 0
#> 29.2 15.45 1 68 1 0
#> 169.1 22.41 1 46 0 0
#> 40.1 18.00 1 28 1 0
#> 43.1 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 81.1 14.06 1 34 0 0
#> 77 7.27 1 67 0 1
#> 187 9.92 1 39 1 0
#> 45.2 17.42 1 54 0 1
#> 70.1 7.38 1 30 1 0
#> 136.1 21.83 1 43 0 1
#> 192.1 16.44 1 31 1 0
#> 16.1 8.71 1 71 0 1
#> 24.1 23.89 1 38 0 0
#> 110 17.56 1 65 0 1
#> 37 12.52 1 57 1 0
#> 159 10.55 1 50 0 1
#> 128.1 20.35 1 35 0 1
#> 70.2 7.38 1 30 1 0
#> 166.1 19.98 1 48 0 0
#> 91 5.33 1 61 0 1
#> 167.1 15.55 1 56 1 0
#> 81.2 14.06 1 34 0 0
#> 76 19.22 1 54 0 1
#> 85 16.44 1 36 0 0
#> 69 23.23 1 25 0 1
#> 61.2 10.12 1 36 0 1
#> 91.1 5.33 1 61 0 1
#> 49.1 12.19 1 48 1 0
#> 88 18.37 1 47 0 0
#> 111.1 17.45 1 47 0 1
#> 50 10.02 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 157.3 15.10 1 47 0 0
#> 169.2 22.41 1 46 0 0
#> 168.1 23.72 1 70 0 0
#> 194.3 22.40 1 38 0 1
#> 5 16.43 1 51 0 1
#> 136.2 21.83 1 43 0 1
#> 79 16.23 1 54 1 0
#> 192.2 16.44 1 31 1 0
#> 41.4 18.02 1 40 1 0
#> 33 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 7 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 46 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 120 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 119.1 24.00 0 17 0 0
#> 73 24.00 0 NA 0 1
#> 73.1 24.00 0 NA 0 1
#> 112 24.00 0 61 0 0
#> 122 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 11.1 24.00 0 42 0 1
#> 138.1 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 148 24.00 0 61 1 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 48 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 71 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 31 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 46.1 24.00 0 71 0 0
#> 28.1 24.00 0 67 1 0
#> 174 24.00 0 49 1 0
#> 82 24.00 0 34 0 0
#> 94 24.00 0 51 0 1
#> 75 24.00 0 21 1 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 132 24.00 0 55 0 0
#> 144.1 24.00 0 28 0 1
#> 146.1 24.00 0 63 1 0
#> 144.2 24.00 0 28 0 1
#> 71.1 24.00 0 51 0 0
#> 46.2 24.00 0 71 0 0
#> 104.1 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 162 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 182 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 165 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 28.2 24.00 0 67 1 0
#> 118.1 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 84.1 24.00 0 39 0 1
#> 200 24.00 0 64 0 0
#> 182.1 24.00 0 35 0 0
#> 64.1 24.00 0 43 0 0
#> 104.2 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 17.1 24.00 0 38 0 1
#> 73.2 24.00 0 NA 0 1
#> 67 24.00 0 25 0 0
#> 176.1 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 62 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 182.2 24.00 0 35 0 0
#> 94.1 24.00 0 51 0 1
#> 7.2 24.00 0 37 1 0
#> 7.3 24.00 0 37 1 0
#> 83.1 24.00 0 6 0 0
#> 20 24.00 0 46 1 0
#> 186.1 24.00 0 45 1 0
#> 21 24.00 0 47 0 0
#> 65.1 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 34 24.00 0 36 0 0
#> 173.1 24.00 0 19 0 1
#> 146.2 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.139 NA NA NA
#> 2 age, Cure model 0.00229 NA NA NA
#> 3 grade_ii, Cure model 0.121 NA NA NA
#> 4 grade_iii, Cure model 0.749 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0110 NA NA NA
#> 2 grade_ii, Survival model 0.791 NA NA NA
#> 3 grade_iii, Survival model 0.706 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.139231 0.002292 0.120851 0.749070
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.2
#> Residual Deviance: 258.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.139230619 0.002291625 0.120851229 0.749070435
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01098683 0.79125168 0.70593887
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9586717 0.6217717 0.5678102 0.6449890 0.7655338 0.7139644 0.7139644
#> [8] 0.3432706 0.9041799 0.6599353 0.7429322 0.7139644 0.2228275 0.6048921
#> [15] 0.9156858 0.9552596 0.2924921 0.6943109 0.9118487 0.8017184 0.8885236
#> [22] 0.9232703 0.8114842 0.8727167 0.6743833 0.8390497 0.7710187 0.5872379
#> [29] 0.6876720 0.8066401 0.6297982 0.7139644 0.6943109 0.7815906 0.4575681
#> [36] 0.9413809 0.8478324 0.4575681 0.8727167 0.9909240 0.7868461 0.4061920
#> [43] 0.4575681 0.6743833 0.5090871 0.9909240 0.7542989 0.8390497 0.5351441
#> [50] 0.8924682 0.5222137 0.3662694 0.9306264 0.3865883 0.7868461 0.9041799
#> [57] 0.8606868 0.9815120 0.6134775 0.1153195 0.8727167 0.8522140 0.9909240
#> [64] 0.9413809 0.8606868 0.5678102 0.5872379 0.8606868 0.4061920 0.7429322
#> [71] 0.9306264 0.9686282 0.8924682 0.9783087 0.9518030 0.7868461 0.9686282
#> [78] 0.5351441 0.8114842 0.9586717 0.1153195 0.7599815 0.9195025 0.9378144
#> [85] 0.6297982 0.9686282 0.6449890 0.9846924 0.8522140 0.8924682 0.6672635
#> [92] 0.8114842 0.3195531 0.9413809 0.9846924 0.9232703 0.7074203 0.7710187
#> [99] 0.9653221 0.8727167 0.4061920 0.2228275 0.4575681 0.8299462 0.5351441
#> [106] 0.8345351 0.8114842 0.7139644 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 16 190 139 166 117 41 41.1 113 60 170 40 41.2 168
#> 8.71 20.81 21.49 19.98 17.46 18.02 18.02 22.86 13.15 19.54 18.00 18.02 23.72
#> 36 177 183 129 8 155 171 96 49 192 157 97 188
#> 21.19 12.53 9.24 23.41 18.43 13.08 16.57 14.54 12.19 16.44 15.10 19.14 16.16
#> 111 153 179 130 128 41.3 8.1 30 194 61 100 194.1 157.1
#> 17.45 21.33 18.63 16.47 20.35 18.02 18.43 17.43 22.40 10.12 16.07 22.40 15.10
#> 127 45 169 194.2 97.1 66 127.1 184 188.1 136 81 175 63
#> 3.53 17.42 22.41 22.40 19.14 22.13 3.53 17.77 16.16 21.83 14.06 21.91 22.77
#> 43 15 45.1 60.1 29 25 90 24 157.2 167 127.2 61.1 29.1
#> 12.10 22.68 17.42 13.15 15.45 6.32 20.94 23.89 15.10 15.55 3.53 10.12 15.45
#> 139.1 153.1 29.2 169.1 40.1 43.1 70 81.1 77 187 45.2 70.1 136.1
#> 21.49 21.33 15.45 22.41 18.00 12.10 7.38 14.06 7.27 9.92 17.42 7.38 21.83
#> 192.1 16.1 24.1 110 37 159 128.1 70.2 166.1 91 167.1 81.2 76
#> 16.44 8.71 23.89 17.56 12.52 10.55 20.35 7.38 19.98 5.33 15.55 14.06 19.22
#> 85 69 61.2 91.1 49.1 88 111.1 149 157.3 169.2 168.1 194.3 5
#> 16.44 23.23 10.12 5.33 12.19 18.37 17.45 8.37 15.10 22.41 23.72 22.40 16.43
#> 136.2 79 192.2 41.4 33 9 138 147 7 11 146 46 95
#> 21.83 16.23 16.44 18.02 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 119 119.1 112 122 142 47 11.1 138.1 7.1 148 104 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 144 48 28 71 147.1 31 35 163 84 46.1 28.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 94 75 131 118 65 64 132 144.1 146.1 144.2 71.1 46.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 116 162 176 182 173 165 160 28.2 118.1 148.1 83 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 182.1 64.1 104.2 186 17.1 67 176.1 62 19 182.2 94.1 7.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.3 83.1 20 186.1 21 65.1 98 34 173.1 146.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[87]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008573185 0.965185355 0.588485426
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.528712943 0.008600349 -0.062365088
#> grade_iii, Cure model
#> 0.897130990
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 13 14.34 1 54 0 1
#> 184 17.77 1 38 0 0
#> 90 20.94 1 50 0 1
#> 184.1 17.77 1 38 0 0
#> 140 12.68 1 59 1 0
#> 4 17.64 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 4.1 17.64 1 NA 0 1
#> 79 16.23 1 54 1 0
#> 77 7.27 1 67 0 1
#> 25 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 150 20.33 1 48 0 0
#> 52 10.42 1 52 0 1
#> 194 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 51 18.23 1 83 0 1
#> 187 9.92 1 39 1 0
#> 108 18.29 1 39 0 1
#> 110 17.56 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 16 8.71 1 71 0 1
#> 57 14.46 1 45 0 1
#> 93 10.33 1 52 0 1
#> 56 12.21 1 60 0 0
#> 55 19.34 1 69 0 1
#> 111 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 168 23.72 1 70 0 0
#> 96 14.54 1 33 0 1
#> 101 9.97 1 10 0 1
#> 32 20.90 1 37 1 0
#> 159 10.55 1 50 0 1
#> 52.1 10.42 1 52 0 1
#> 187.1 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 77.1 7.27 1 67 0 1
#> 89 11.44 1 NA 0 0
#> 150.1 20.33 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 157.1 15.10 1 47 0 0
#> 8 18.43 1 32 0 0
#> 190 20.81 1 42 1 0
#> 188 16.16 1 46 0 1
#> 157.2 15.10 1 47 0 0
#> 171 16.57 1 41 0 1
#> 149.1 8.37 1 33 1 0
#> 134 17.81 1 47 1 0
#> 92 22.92 1 47 0 1
#> 188.1 16.16 1 46 0 1
#> 23 16.92 1 61 0 0
#> 100 16.07 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 171.1 16.57 1 41 0 1
#> 110.1 17.56 1 65 0 1
#> 154 12.63 1 20 1 0
#> 23.1 16.92 1 61 0 0
#> 66 22.13 1 53 0 0
#> 99 21.19 1 38 0 1
#> 159.1 10.55 1 50 0 1
#> 16.1 8.71 1 71 0 1
#> 25.1 6.32 1 34 1 0
#> 170.1 19.54 1 43 0 1
#> 125 15.65 1 67 1 0
#> 169 22.41 1 46 0 0
#> 194.2 22.40 1 38 0 1
#> 168.1 23.72 1 70 0 0
#> 184.2 17.77 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 145.1 10.07 1 65 1 0
#> 189 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 13.1 14.34 1 54 0 1
#> 190.1 20.81 1 42 1 0
#> 8.1 18.43 1 32 0 0
#> 99.1 21.19 1 38 0 1
#> 157.3 15.10 1 47 0 0
#> 43 12.10 1 61 0 1
#> 111.1 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 37 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 23.2 16.92 1 61 0 0
#> 105 19.75 1 60 0 0
#> 49 12.19 1 48 1 0
#> 25.2 6.32 1 34 1 0
#> 175 21.91 1 43 0 0
#> 85.1 16.44 1 36 0 0
#> 69 23.23 1 25 0 1
#> 145.2 10.07 1 65 1 0
#> 56.1 12.21 1 60 0 0
#> 159.2 10.55 1 50 0 1
#> 99.2 21.19 1 38 0 1
#> 175.1 21.91 1 43 0 0
#> 93.1 10.33 1 52 0 1
#> 139 21.49 1 63 1 0
#> 90.1 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 128 20.35 1 35 0 1
#> 4.2 17.64 1 NA 0 1
#> 57.2 14.46 1 45 0 1
#> 159.3 10.55 1 50 0 1
#> 181 16.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 43.1 12.10 1 61 0 1
#> 158 20.14 1 74 1 0
#> 65 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 163 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 1 24.00 0 23 1 0
#> 148 24.00 0 61 1 0
#> 44 24.00 0 56 0 0
#> 27 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 83 24.00 0 6 0 0
#> 2 24.00 0 9 0 0
#> 44.1 24.00 0 56 0 0
#> 19.1 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 147 24.00 0 76 1 0
#> 12 24.00 0 63 0 0
#> 74 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 83.1 24.00 0 6 0 0
#> 174 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 19.2 24.00 0 57 0 1
#> 178 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 20 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 165 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 193 24.00 0 45 0 1
#> 19.3 24.00 0 57 0 1
#> 31 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 200.1 24.00 0 64 0 0
#> 185 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 112.1 24.00 0 61 0 0
#> 65.1 24.00 0 57 1 0
#> 20.1 24.00 0 46 1 0
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 121.1 24.00 0 57 1 0
#> 31.1 24.00 0 36 0 1
#> 152 24.00 0 36 0 1
#> 82.1 24.00 0 34 0 0
#> 143 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 54 24.00 0 53 1 0
#> 74.1 24.00 0 43 0 1
#> 27.1 24.00 0 63 1 0
#> 12.1 24.00 0 63 0 0
#> 46 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 109.1 24.00 0 48 0 0
#> 126 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 104 24.00 0 50 1 0
#> 12.2 24.00 0 63 0 0
#> 115 24.00 0 NA 1 0
#> 131 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 186 24.00 0 45 1 0
#> 138 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 182 24.00 0 35 0 0
#> 84.1 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 109.2 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 7.1 24.00 0 37 1 0
#> 67.1 24.00 0 25 0 0
#> 65.2 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 132.1 24.00 0 55 0 0
#> 173 24.00 0 19 0 1
#> 126.1 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.529 NA NA NA
#> 2 age, Cure model 0.00860 NA NA NA
#> 3 grade_ii, Cure model -0.0624 NA NA NA
#> 4 grade_iii, Cure model 0.897 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00857 NA NA NA
#> 2 grade_ii, Survival model 0.965 NA NA NA
#> 3 grade_iii, Survival model 0.588 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.52871 0.00860 -0.06237 0.89713
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 253.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.528712943 0.008600349 -0.062365088 0.897130990
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008573185 0.965185355 0.588485426
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.08893498 0.85425914 0.67829743 0.50934085 0.67829743 0.86900348
#> [7] 0.97472827 0.77378741 0.98212439 0.98940001 0.64913478 0.57683683
#> [13] 0.92717216 0.33143573 0.81311961 0.66410551 0.95951366 0.65668483
#> [19] 0.69879944 0.61074278 0.96719009 0.83917471 0.93555090 0.88777315
#> [25] 0.62638305 0.71197955 0.94379576 0.18307004 0.83396062 0.95558370
#> [31] 0.53046235 0.91021381 0.92717216 0.95951366 0.76178898 0.98212439
#> [37] 0.57683683 0.33143573 0.80779008 0.81311961 0.63403587 0.54059929
#> [43] 0.77966500 0.81311961 0.74350358 0.97472827 0.67131125 0.28070189
#> [49] 0.77966500 0.72475868 0.79108897 0.83917471 0.45110838 0.74350358
#> [55] 0.69879944 0.87378861 0.72475868 0.38419255 0.46478179 0.91021381
#> [61] 0.96719009 0.98940001 0.61074278 0.79679392 0.30657508 0.33143573
#> [67] 0.18307004 0.67829743 0.08893498 0.94379576 0.86412832 0.85425914
#> [73] 0.54059929 0.63403587 0.46478179 0.81311961 0.90140365 0.71197955
#> [79] 0.88316715 0.87851892 0.80235309 0.72475868 0.60253246 0.89689775
#> [85] 0.98940001 0.40215464 0.76178898 0.25004540 0.94379576 0.88777315
#> [91] 0.91021381 0.46478179 0.40215464 0.93555090 0.43596297 0.50934085
#> [97] 0.46478179 0.56792754 0.83917471 0.91021381 0.75573133 0.55881357
#> [103] 0.90140365 0.59424620 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 24 13 184 90 184.1 140 149 79 77 25 88 150 52
#> 23.89 14.34 17.77 20.94 17.77 12.68 8.37 16.23 7.27 6.32 18.37 20.33 10.42
#> 194 157 51 187 108 110 170 16 57 93 56 55 111
#> 22.40 15.10 18.23 9.92 18.29 17.56 19.54 8.71 14.46 10.33 12.21 19.34 17.45
#> 145 168 96 101 32 159 52.1 187.1 85 77.1 150.1 194.1 18
#> 10.07 23.72 14.54 9.97 20.90 10.55 10.42 9.92 16.44 7.27 20.33 22.40 15.21
#> 157.1 8 190 188 157.2 171 149.1 134 92 188.1 23 100 57.1
#> 15.10 18.43 20.81 16.16 15.10 16.57 8.37 17.81 22.92 16.16 16.92 16.07 14.46
#> 153 171.1 110.1 154 23.1 66 99 159.1 16.1 25.1 170.1 125 169
#> 21.33 16.57 17.56 12.63 16.92 22.13 21.19 10.55 8.71 6.32 19.54 15.65 22.41
#> 194.2 168.1 184.2 24.1 145.1 60 13.1 190.1 8.1 99.1 157.3 43 111.1
#> 22.40 23.72 17.77 23.89 10.07 13.15 14.34 20.81 18.43 21.19 15.10 12.10 17.45
#> 42 37 167 23.2 105 49 25.2 175 85.1 69 145.2 56.1 159.2
#> 12.43 12.52 15.55 16.92 19.75 12.19 6.32 21.91 16.44 23.23 10.07 12.21 10.55
#> 99.2 175.1 93.1 139 90.1 36 128 57.2 159.3 181 68 43.1 158
#> 21.19 21.91 10.33 21.49 20.94 21.19 20.35 14.46 10.55 16.46 20.62 12.10 20.14
#> 65 196 163 200 1 148 44 27 156 17 19 83 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 19.1 7 147 12 74 28 83.1 174 160 80 19.2 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 20 198 165 109 11 193 19.3 31 38 121 200.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 112.1 65.1 20.1 176 64 121.1 31.1 152 82.1 143 38.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 3 132 54 74.1 27.1 12.1 46 98 109.1 126 48 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 12.2 131 72 186 138 84 146 116 182 84.1 67 109.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 47 7.1 67.1 65.2 95 132.1 173 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[88]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003371053 0.599480054 0.195395774
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.470172672 0.004796185 0.158816975
#> grade_iii, Cure model
#> 1.401393422
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 36 21.19 1 48 0 1
#> 52 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 40 18.00 1 28 1 0
#> 99 21.19 1 38 0 1
#> 100 16.07 1 60 0 0
#> 113 22.86 1 34 0 0
#> 68 20.62 1 44 0 0
#> 181.1 16.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 111 17.45 1 47 0 1
#> 97 19.14 1 65 0 1
#> 90 20.94 1 50 0 1
#> 36.1 21.19 1 48 0 1
#> 58 19.34 1 39 0 0
#> 77 7.27 1 67 0 1
#> 124 9.73 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 51 18.23 1 83 0 1
#> 125 15.65 1 67 1 0
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 192 16.44 1 31 1 0
#> 183 9.24 1 67 1 0
#> 110 17.56 1 65 0 1
#> 37 12.52 1 57 1 0
#> 113.1 22.86 1 34 0 0
#> 45 17.42 1 54 0 1
#> 69 23.23 1 25 0 1
#> 171 16.57 1 41 0 1
#> 23 16.92 1 61 0 0
#> 108 18.29 1 39 0 1
#> 18 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 179 18.63 1 42 0 0
#> 41 18.02 1 40 1 0
#> 93 10.33 1 52 0 1
#> 100.1 16.07 1 60 0 0
#> 66 22.13 1 53 0 0
#> 134 17.81 1 47 1 0
#> 101 9.97 1 10 0 1
#> 86 23.81 1 58 0 1
#> 45.1 17.42 1 54 0 1
#> 125.1 15.65 1 67 1 0
#> 127 3.53 1 62 0 1
#> 155 13.08 1 26 0 0
#> 23.1 16.92 1 61 0 0
#> 43 12.10 1 61 0 1
#> 40.1 18.00 1 28 1 0
#> 139 21.49 1 63 1 0
#> 36.2 21.19 1 48 0 1
#> 68.1 20.62 1 44 0 0
#> 194 22.40 1 38 0 1
#> 127.1 3.53 1 62 0 1
#> 78 23.88 1 43 0 0
#> 175 21.91 1 43 0 0
#> 40.2 18.00 1 28 1 0
#> 150 20.33 1 48 0 0
#> 85 16.44 1 36 0 0
#> 111.1 17.45 1 47 0 1
#> 99.1 21.19 1 38 0 1
#> 108.1 18.29 1 39 0 1
#> 97.1 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 81 14.06 1 34 0 0
#> 69.1 23.23 1 25 0 1
#> 105 19.75 1 60 0 0
#> 177 12.53 1 75 0 0
#> 32 20.90 1 37 1 0
#> 145 10.07 1 65 1 0
#> 13.1 14.34 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 14 12.89 1 21 0 0
#> 164 23.60 1 76 0 1
#> 79.1 16.23 1 54 1 0
#> 123 13.00 1 44 1 0
#> 55 19.34 1 69 0 1
#> 32.1 20.90 1 37 1 0
#> 134.1 17.81 1 47 1 0
#> 40.3 18.00 1 28 1 0
#> 37.1 12.52 1 57 1 0
#> 43.1 12.10 1 61 0 1
#> 40.4 18.00 1 28 1 0
#> 136 21.83 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 43.2 12.10 1 61 0 1
#> 88 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 52.1 10.42 1 52 0 1
#> 15 22.68 1 48 0 0
#> 25 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 101.1 9.97 1 10 0 1
#> 32.2 20.90 1 37 1 0
#> 52.2 10.42 1 52 0 1
#> 190 20.81 1 42 1 0
#> 194.1 22.40 1 38 0 1
#> 194.2 22.40 1 38 0 1
#> 37.2 12.52 1 57 1 0
#> 29 15.45 1 68 1 0
#> 79.2 16.23 1 54 1 0
#> 40.5 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 86.1 23.81 1 58 0 1
#> 105.1 19.75 1 60 0 0
#> 161 24.00 0 45 0 0
#> 98 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 141 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 196.1 24.00 0 19 0 0
#> 27 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 196.2 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 9 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 62 24.00 0 71 0 0
#> 35.1 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 53 24.00 0 32 0 1
#> 198 24.00 0 66 0 1
#> 142.1 24.00 0 53 0 0
#> 186.1 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 198.1 24.00 0 66 0 1
#> 160 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 198.2 24.00 0 66 0 1
#> 35.2 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 64 24.00 0 43 0 0
#> 182 24.00 0 35 0 0
#> 20 24.00 0 46 1 0
#> 161.1 24.00 0 45 0 0
#> 144 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 132 24.00 0 55 0 0
#> 185 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 80 24.00 0 41 0 0
#> 161.2 24.00 0 45 0 0
#> 143.1 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 82.1 24.00 0 34 0 0
#> 143.2 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 22.1 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 182.1 24.00 0 35 0 0
#> 82.2 24.00 0 34 0 0
#> 115.1 24.00 0 NA 1 0
#> 116.1 24.00 0 58 0 1
#> 31 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 144.1 24.00 0 28 0 1
#> 20.1 24.00 0 46 1 0
#> 132.1 24.00 0 55 0 0
#> 7 24.00 0 37 1 0
#> 147.1 24.00 0 76 1 0
#> 11 24.00 0 42 0 1
#> 141.1 24.00 0 44 1 0
#> 27.2 24.00 0 63 1 0
#> 103.1 24.00 0 56 1 0
#> 98.1 24.00 0 34 1 0
#> 75 24.00 0 21 1 0
#> 74.1 24.00 0 43 0 1
#> 160.1 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 104.1 24.00 0 50 1 0
#> 7.1 24.00 0 37 1 0
#> 122 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 186.2 24.00 0 45 1 0
#> 104.2 24.00 0 50 1 0
#> 65.1 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.470 NA NA NA
#> 2 age, Cure model 0.00480 NA NA NA
#> 3 grade_ii, Cure model 0.159 NA NA NA
#> 4 grade_iii, Cure model 1.40 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00337 NA NA NA
#> 2 grade_ii, Survival model 0.599 NA NA NA
#> 3 grade_iii, Survival model 0.195 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.470173 0.004796 0.158817 1.401393
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 248.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.470172672 0.004796185 0.158816975 1.401393422
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003371053 0.599480054 0.195395774
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79734152 0.34770535 0.91122680 0.71486804 0.77727487 0.59681919
#> [7] 0.34770535 0.76366982 0.15158142 0.44661381 0.71486804 0.97106855
#> [13] 0.29977224 0.66397275 0.52828300 0.39814598 0.34770535 0.50168419
#> [19] 0.97691103 0.88680135 0.82353976 0.57996343 0.78408145 0.95926404
#> [25] 0.81705186 0.72914976 0.96518944 0.65652565 0.86834730 0.15158142
#> [31] 0.67864451 0.11922283 0.70763086 0.69317227 0.56295077 0.81054542
#> [37] 0.74327232 0.54558004 0.58845673 0.92930504 0.76366982 0.25690337
#> [43] 0.64162963 0.94737097 0.06148186 0.67864451 0.78408145 0.98852374
#> [49] 0.84280708 0.69317227 0.89298618 0.59681919 0.32431623 0.34770535
#> [55] 0.44661381 0.21547829 0.98852374 0.02588545 0.27136770 0.59681919
#> [61] 0.46523691 0.72914976 0.66397275 0.34770535 0.56295077 0.52828300
#> [67] 0.51941210 0.47461028 0.83637212 0.11922283 0.48374250 0.86198756
#> [73] 0.40866460 0.94138624 0.82353976 0.29977224 0.85561429 0.09998754
#> [79] 0.74327232 0.84923754 0.50168419 0.40866460 0.64162963 0.59681919
#> [85] 0.86834730 0.89298618 0.59681919 0.28571297 0.89298618 0.55427709
#> [91] 0.19942368 0.91122680 0.18315015 0.98273526 0.33625309 0.94737097
#> [97] 0.40866460 0.91122680 0.43713934 0.21547829 0.21547829 0.86834730
#> [103] 0.80397844 0.74327232 0.59681919 0.93535291 0.06148186 0.48374250
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 39 36 52 181 26 40 99 100 113 68 181.1 149 197
#> 15.59 21.19 10.42 16.46 15.77 18.00 21.19 16.07 22.86 20.62 16.46 8.37 21.60
#> 111 97 90 36.1 58 77 56 13 51 125 187 96 192
#> 17.45 19.14 20.94 21.19 19.34 7.27 12.21 14.34 18.23 15.65 9.92 14.54 16.44
#> 183 110 37 113.1 45 69 171 23 108 18 79 179 41
#> 9.24 17.56 12.52 22.86 17.42 23.23 16.57 16.92 18.29 15.21 16.23 18.63 18.02
#> 93 100.1 66 134 101 86 45.1 125.1 127 155 23.1 43 40.1
#> 10.33 16.07 22.13 17.81 9.97 23.81 17.42 15.65 3.53 13.08 16.92 12.10 18.00
#> 139 36.2 68.1 194 127.1 78 175 40.2 150 85 111.1 99.1 108.1
#> 21.49 21.19 20.62 22.40 3.53 23.88 21.91 18.00 20.33 16.44 17.45 21.19 18.29
#> 97.1 76 158 81 69.1 105 177 32 145 13.1 197.1 14 164
#> 19.14 19.22 20.14 14.06 23.23 19.75 12.53 20.90 10.07 14.34 21.60 12.89 23.60
#> 79.1 123 55 32.1 134.1 40.3 37.1 43.1 40.4 136 43.2 88 169
#> 16.23 13.00 19.34 20.90 17.81 18.00 12.52 12.10 18.00 21.83 12.10 18.37 22.41
#> 52.1 15 25 153 101.1 32.2 52.2 190 194.1 194.2 37.2 29 79.2
#> 10.42 22.68 6.32 21.33 9.97 20.90 10.42 20.81 22.40 22.40 12.52 15.45 16.23
#> 40.5 61 86.1 105.1 161 98 196 141 35 104 143 118 137
#> 18.00 10.12 23.81 19.75 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 196.1 27 47 142 196.2 200 9 186 165 146 33 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 62 35.1 65 103 53 198 142.1 186.1 22 198.1 160 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 198.2 35.2 116 64 182 20 161.1 144 82 132 185 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 161.2 143.1 9.1 27.1 102 82.1 143.2 193 22.1 121 182.1 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 31 178 144.1 20.1 132.1 7 147.1 11 141.1 27.2 103.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 74.1 160.1 137.1 104.1 7.1 122 67 186.2 104.2 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[89]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001293995 0.684714536 0.411261459
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.340569811 0.004135915 0.063251434
#> grade_iii, Cure model
#> 0.976211640
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 168 23.72 1 70 0 0
#> 190 20.81 1 42 1 0
#> 110 17.56 1 65 0 1
#> 16 8.71 1 71 0 1
#> 105 19.75 1 60 0 0
#> 194 22.40 1 38 0 1
#> 70 7.38 1 30 1 0
#> 134 17.81 1 47 1 0
#> 130 16.47 1 53 0 1
#> 88 18.37 1 47 0 0
#> 52 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 136.1 21.83 1 43 0 1
#> 166 19.98 1 48 0 0
#> 70.1 7.38 1 30 1 0
#> 107 11.18 1 54 1 0
#> 61 10.12 1 36 0 1
#> 59 10.16 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 63 22.77 1 31 1 0
#> 68 20.62 1 44 0 0
#> 171 16.57 1 41 0 1
#> 29 15.45 1 68 1 0
#> 150 20.33 1 48 0 0
#> 42 12.43 1 49 0 1
#> 68.1 20.62 1 44 0 0
#> 129 23.41 1 53 1 0
#> 153 21.33 1 55 1 0
#> 93 10.33 1 52 0 1
#> 167 15.55 1 56 1 0
#> 18 15.21 1 49 1 0
#> 97 19.14 1 65 0 1
#> 69 23.23 1 25 0 1
#> 52.1 10.42 1 52 0 1
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 49 12.19 1 48 1 0
#> 79 16.23 1 54 1 0
#> 170 19.54 1 43 0 1
#> 49.1 12.19 1 48 1 0
#> 52.2 10.42 1 52 0 1
#> 100 16.07 1 60 0 0
#> 159 10.55 1 50 0 1
#> 50 10.02 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 26 15.77 1 49 0 1
#> 68.2 20.62 1 44 0 0
#> 153.1 21.33 1 55 1 0
#> 85 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 159.1 10.55 1 50 0 1
#> 88.1 18.37 1 47 0 0
#> 164 23.60 1 76 0 1
#> 167.1 15.55 1 56 1 0
#> 134.1 17.81 1 47 1 0
#> 96 14.54 1 33 0 1
#> 15.1 22.68 1 48 0 0
#> 134.2 17.81 1 47 1 0
#> 189 10.51 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 154.1 12.63 1 20 1 0
#> 91 5.33 1 61 0 1
#> 125 15.65 1 67 1 0
#> 130.1 16.47 1 53 0 1
#> 23 16.92 1 61 0 0
#> 133 14.65 1 57 0 0
#> 194.1 22.40 1 38 0 1
#> 125.1 15.65 1 67 1 0
#> 30 17.43 1 78 0 0
#> 59.1 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 171.1 16.57 1 41 0 1
#> 52.3 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 52.4 10.42 1 52 0 1
#> 6 15.64 1 39 0 0
#> 30.1 17.43 1 78 0 0
#> 76 19.22 1 54 0 1
#> 52.5 10.42 1 52 0 1
#> 55 19.34 1 69 0 1
#> 127 3.53 1 62 0 1
#> 77 7.27 1 67 0 1
#> 145 10.07 1 65 1 0
#> 111 17.45 1 47 0 1
#> 70.2 7.38 1 30 1 0
#> 157 15.10 1 47 0 0
#> 113 22.86 1 34 0 0
#> 8 18.43 1 32 0 0
#> 49.2 12.19 1 48 1 0
#> 49.3 12.19 1 48 1 0
#> 113.1 22.86 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 86.1 23.81 1 58 0 1
#> 59.2 10.16 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 150.1 20.33 1 48 0 0
#> 159.2 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 49.4 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 60 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 139.1 21.49 1 63 1 0
#> 78 23.88 1 43 0 0
#> 105.1 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 51 18.23 1 83 0 1
#> 113.2 22.86 1 34 0 0
#> 93.1 10.33 1 52 0 1
#> 193 24.00 0 45 0 1
#> 151 24.00 0 42 0 0
#> 135 24.00 0 58 1 0
#> 146 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 98 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 120 24.00 0 68 0 1
#> 98.1 24.00 0 34 1 0
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 138 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 9 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 172 24.00 0 41 0 0
#> 146.1 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 31 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 67 24.00 0 25 0 0
#> 7.1 24.00 0 37 1 0
#> 161 24.00 0 45 0 0
#> 103 24.00 0 56 1 0
#> 143 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 132 24.00 0 55 0 0
#> 48 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 103.1 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 28 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 7.2 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 186 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 122.1 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 22.1 24.00 0 52 1 0
#> 146.2 24.00 0 63 1 0
#> 161.1 24.00 0 45 0 0
#> 162 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 11.2 24.00 0 42 0 1
#> 142.1 24.00 0 53 0 0
#> 163.1 24.00 0 66 0 0
#> 12.1 24.00 0 63 0 0
#> 163.2 24.00 0 66 0 0
#> 95.2 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 176 24.00 0 43 0 1
#> 126.1 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 95.3 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 71.1 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 126.2 24.00 0 48 0 0
#> 126.3 24.00 0 48 0 0
#> 146.3 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 174.1 24.00 0 49 1 0
#> 143.1 24.00 0 51 0 0
#> 126.4 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 84.1 24.00 0 39 0 1
#> 174.2 24.00 0 49 1 0
#> 83 24.00 0 6 0 0
#> 200.2 24.00 0 64 0 0
#> 104.1 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.341 NA NA NA
#> 2 age, Cure model 0.00414 NA NA NA
#> 3 grade_ii, Cure model 0.0633 NA NA NA
#> 4 grade_iii, Cure model 0.976 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00129 NA NA NA
#> 2 grade_ii, Survival model 0.685 NA NA NA
#> 3 grade_iii, Survival model 0.411 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.340570 0.004136 0.063251 0.976212
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 257.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.340569811 0.004135915 0.063251434 0.976211640
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001293995 0.684714536 0.411261459
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.10476891 0.36549144 0.58304505 0.95262350 0.43466065 0.27402505
#> [7] 0.96473664 0.55774802 0.64130807 0.51162366 0.89135270 0.29908851
#> [13] 0.29908851 0.42468410 0.96473664 0.85940420 0.94037264 0.95870054
#> [19] 0.23384056 0.37558774 0.62493939 0.74209602 0.40493600 0.80631770
#> [25] 0.37558774 0.14521860 0.34496625 0.92806956 0.72736556 0.74941309
#> [31] 0.48334835 0.16190592 0.89135270 0.85281237 0.24754833 0.82020184
#> [37] 0.68125981 0.45431294 0.82020184 0.89135270 0.68909721 0.87231499
#> [43] 0.49278266 0.69692742 0.37558774 0.34496625 0.66547171 0.78542339
#> [49] 0.87231499 0.51162366 0.12606317 0.72736556 0.55774802 0.77111441
#> [55] 0.24754833 0.55774802 0.85940420 0.65742348 0.81326216 0.78542339
#> [61] 0.98827706 0.70470456 0.64130807 0.61657036 0.76388557 0.27402505
#> [67] 0.70470456 0.59992749 0.32296325 0.62493939 0.89135270 0.06587128
#> [73] 0.89135270 0.71978803 0.59992749 0.47379450 0.89135270 0.46412011
#> [79] 0.99414950 0.98238246 0.94652101 0.59152260 0.96473664 0.75665150
#> [85] 0.19266720 0.50220689 0.82020184 0.82020184 0.19266720 0.06587128
#> [91] 0.53024139 0.40493600 0.87231499 0.79933672 0.82020184 0.66547171
#> [97] 0.77830451 0.17768724 0.32296325 0.02558035 0.43466065 0.54872465
#> [103] 0.53953682 0.19266720 0.92806956 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 168 190 110 16 105 194 70 134 130 88 52 136 136.1
#> 23.72 20.81 17.56 8.71 19.75 22.40 7.38 17.81 16.47 18.37 10.42 21.83 21.83
#> 166 70.1 107 61 149 63 68 171 29 150 42 68.1 129
#> 19.98 7.38 11.18 10.12 8.37 22.77 20.62 16.57 15.45 20.33 12.43 20.62 23.41
#> 153 93 167 18 97 69 52.1 43 15 49 79 170 49.1
#> 21.33 10.33 15.55 15.21 19.14 23.23 10.42 12.10 22.68 12.19 16.23 19.54 12.19
#> 52.2 100 159 179 26 68.2 153.1 85 154 159.1 88.1 164 167.1
#> 10.42 16.07 10.55 18.63 15.77 20.62 21.33 16.44 12.63 10.55 18.37 23.60 15.55
#> 134.1 96 15.1 134.2 107.1 181 56 154.1 91 125 130.1 23 133
#> 17.81 14.54 22.68 17.81 11.18 16.46 12.21 12.63 5.33 15.65 16.47 16.92 14.65
#> 194.1 125.1 30 139 171.1 52.3 86 52.4 6 30.1 76 52.5 55
#> 22.40 15.65 17.43 21.49 16.57 10.42 23.81 10.42 15.64 17.43 19.22 10.42 19.34
#> 127 77 145 111 70.2 157 113 8 49.2 49.3 113.1 86.1 108
#> 3.53 7.27 10.07 17.45 7.38 15.10 22.86 18.43 12.19 12.19 22.86 23.81 18.29
#> 150.1 159.2 177 49.4 192 60 92 139.1 78 105.1 41 51 113.2
#> 20.33 10.55 12.53 12.19 16.44 13.15 22.92 21.49 23.88 19.75 18.02 18.23 22.86
#> 93.1 193 151 135 146 178 11 98 74 64 120 98.1 122
#> 10.33 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 138 178.1 54 9 20 22 54.1 198 172 146.1 95 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 126 7 67 7.1 161 103 143 21 165 75 132 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 12 103.1 44 28 3 95.1 144 7.2 142 163 28.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 122.1 160 71 22.1 146.2 161.1 162 11.1 11.2 142.1 163.1 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.2 95.2 84 176 126.1 9.1 95.3 141 71.1 200.1 126.2 126.3 146.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 174.1 143.1 126.4 38 75.1 84.1 174.2 83 200.2 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[90]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004337145 0.465010149 0.265204677
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.48818454 0.01087969 -0.14729105
#> grade_iii, Cure model
#> 0.66703755
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 136 21.83 1 43 0 1
#> 108 18.29 1 39 0 1
#> 39 15.59 1 37 0 1
#> 86 23.81 1 58 0 1
#> 5 16.43 1 51 0 1
#> 63 22.77 1 31 1 0
#> 81 14.06 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 199 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 51 18.23 1 83 0 1
#> 128 20.35 1 35 0 1
#> 154 12.63 1 20 1 0
#> 96 14.54 1 33 0 1
#> 194 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 181 16.46 1 45 0 1
#> 179 18.63 1 42 0 0
#> 100 16.07 1 60 0 0
#> 51.1 18.23 1 83 0 1
#> 168 23.72 1 70 0 0
#> 179.1 18.63 1 42 0 0
#> 40 18.00 1 28 1 0
#> 100.1 16.07 1 60 0 0
#> 136.1 21.83 1 43 0 1
#> 29 15.45 1 68 1 0
#> 45 17.42 1 54 0 1
#> 49 12.19 1 48 1 0
#> 43 12.10 1 61 0 1
#> 184 17.77 1 38 0 0
#> 192 16.44 1 31 1 0
#> 139 21.49 1 63 1 0
#> 32 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 125.1 15.65 1 67 1 0
#> 184.1 17.77 1 38 0 0
#> 183 9.24 1 67 1 0
#> 86.1 23.81 1 58 0 1
#> 101 9.97 1 10 0 1
#> 136.2 21.83 1 43 0 1
#> 195 11.76 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 5.1 16.43 1 51 0 1
#> 117 17.46 1 26 0 1
#> 139.1 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 189 10.51 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 106 16.67 1 49 1 0
#> 5.2 16.43 1 51 0 1
#> 183.1 9.24 1 67 1 0
#> 127 3.53 1 62 0 1
#> 78 23.88 1 43 0 0
#> 169 22.41 1 46 0 0
#> 81.2 14.06 1 34 0 0
#> 77 7.27 1 67 0 1
#> 43.1 12.10 1 61 0 1
#> 91 5.33 1 61 0 1
#> 6 15.64 1 39 0 0
#> 24 23.89 1 38 0 0
#> 158 20.14 1 74 1 0
#> 69 23.23 1 25 0 1
#> 81.3 14.06 1 34 0 0
#> 56 12.21 1 60 0 0
#> 164 23.60 1 76 0 1
#> 184.2 17.77 1 38 0 0
#> 153 21.33 1 55 1 0
#> 136.3 21.83 1 43 0 1
#> 113 22.86 1 34 0 0
#> 128.1 20.35 1 35 0 1
#> 180 14.82 1 37 0 0
#> 93 10.33 1 52 0 1
#> 18 15.21 1 49 1 0
#> 169.1 22.41 1 46 0 0
#> 63.1 22.77 1 31 1 0
#> 90 20.94 1 50 0 1
#> 30 17.43 1 78 0 0
#> 26.1 15.77 1 49 0 1
#> 180.1 14.82 1 37 0 0
#> 4.1 17.64 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 42 12.43 1 49 0 1
#> 25 6.32 1 34 1 0
#> 69.1 23.23 1 25 0 1
#> 159.1 10.55 1 50 0 1
#> 184.3 17.77 1 38 0 0
#> 26.2 15.77 1 49 0 1
#> 63.2 22.77 1 31 1 0
#> 130 16.47 1 53 0 1
#> 26.3 15.77 1 49 0 1
#> 45.1 17.42 1 54 0 1
#> 86.2 23.81 1 58 0 1
#> 188 16.16 1 46 0 1
#> 43.2 12.10 1 61 0 1
#> 108.1 18.29 1 39 0 1
#> 197 21.60 1 69 1 0
#> 43.3 12.10 1 61 0 1
#> 134 17.81 1 47 1 0
#> 188.1 16.16 1 46 0 1
#> 184.4 17.77 1 38 0 0
#> 37 12.52 1 57 1 0
#> 134.1 17.81 1 47 1 0
#> 58 19.34 1 39 0 0
#> 57 14.46 1 45 0 1
#> 106.1 16.67 1 49 1 0
#> 55 19.34 1 69 0 1
#> 123 13.00 1 44 1 0
#> 60 13.15 1 38 1 0
#> 23.1 16.92 1 61 0 0
#> 78.1 23.88 1 43 0 0
#> 169.2 22.41 1 46 0 0
#> 98 24.00 0 34 1 0
#> 62 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 122 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 198 24.00 0 66 0 1
#> 142 24.00 0 53 0 0
#> 1 24.00 0 23 1 0
#> 20 24.00 0 46 1 0
#> 162 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 173.1 24.00 0 19 0 1
#> 142.1 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 109 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 48.1 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 95 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 19 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 120.1 24.00 0 68 0 1
#> 20.1 24.00 0 46 1 0
#> 46 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 48.2 24.00 0 31 1 0
#> 21.2 24.00 0 47 0 0
#> 65.2 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 182.1 24.00 0 35 0 0
#> 172 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 143 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 27.1 24.00 0 63 1 0
#> 73.1 24.00 0 NA 0 1
#> 186 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 94.1 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 28 24.00 0 67 1 0
#> 148 24.00 0 61 1 0
#> 3 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 186.1 24.00 0 45 1 0
#> 198.1 24.00 0 66 0 1
#> 7 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 84 24.00 0 39 0 1
#> 132 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 84.1 24.00 0 39 0 1
#> 2.2 24.00 0 9 0 0
#> 34 24.00 0 36 0 0
#> 120.2 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 74 24.00 0 43 0 1
#> 83.1 24.00 0 6 0 0
#> 144.1 24.00 0 28 0 1
#> 200.1 24.00 0 64 0 0
#> 141.1 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 109.1 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 20.2 24.00 0 46 1 0
#> 27.2 24.00 0 63 1 0
#> 28.2 24.00 0 67 1 0
#> 115 24.00 0 NA 1 0
#> 174 24.00 0 49 1 0
#> 173.3 24.00 0 19 0 1
#> 109.2 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.488 NA NA NA
#> 2 age, Cure model 0.0109 NA NA NA
#> 3 grade_ii, Cure model -0.147 NA NA NA
#> 4 grade_iii, Cure model 0.667 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00434 NA NA NA
#> 2 grade_ii, Survival model 0.465 NA NA NA
#> 3 grade_iii, Survival model 0.265 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.48818 0.01088 -0.14729 0.66704
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 256.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.48818454 0.01087969 -0.14729105 0.66703755
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004337145 0.465010149 0.265204677
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.34221562 0.52435608 0.80027033 0.11769109 0.70358020 0.25880006
#> [7] 0.84634286 0.75295948 0.54134199 0.45340692 0.88480431 0.83328664
#> [13] 0.33025667 0.78010897 0.65146193 0.68890718 0.50706557 0.73894795
#> [19] 0.54134199 0.16668950 0.50706557 0.55787731 0.73894795 0.34221562
#> [25] 0.80697293 0.63617492 0.91003738 0.91626942 0.58201593 0.69627543
#> [31] 0.39508261 0.44402843 0.22983567 0.78010897 0.58201593 0.96464831
#> [37] 0.11769109 0.95862127 0.34221562 0.84634286 0.70358020 0.62051101
#> [43] 0.39508261 0.94048887 0.47158497 0.66664107 0.70358020 0.96464831
#> [49] 0.99416243 0.06741302 0.29500275 0.84634286 0.97649809 0.91626942
#> [55] 0.98830056 0.79353780 0.02886947 0.48072217 0.20058538 0.84634286
#> [61] 0.90376408 0.18426898 0.58201593 0.41496749 0.34221562 0.24438590
#> [67] 0.45340692 0.82020051 0.95258051 0.81361277 0.29500275 0.25880006
#> [73] 0.43447458 0.62836261 0.75295948 0.82020051 0.42478882 0.89747781
#> [79] 0.98241430 0.20058538 0.94048887 0.58201593 0.75295948 0.25880006
#> [85] 0.68149257 0.75295948 0.63617492 0.11769109 0.72485700 0.91626942
#> [91] 0.52435608 0.38441812 0.91626942 0.56610913 0.72485700 0.58201593
#> [97] 0.89116446 0.56610913 0.48965653 0.83982959 0.66664107 0.48965653
#> [103] 0.87841033 0.87197292 0.65146193 0.06741302 0.29500275 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 136 108 39 86 5 63 81 26 51 128 154 96 194
#> 21.83 18.29 15.59 23.81 16.43 22.77 14.06 15.77 18.23 20.35 12.63 14.54 22.40
#> 125 23 181 179 100 51.1 168 179.1 40 100.1 136.1 29 45
#> 15.65 16.92 16.46 18.63 16.07 18.23 23.72 18.63 18.00 16.07 21.83 15.45 17.42
#> 49 43 184 192 139 32 92 125.1 184.1 183 86.1 101 136.2
#> 12.19 12.10 17.77 16.44 21.49 20.90 22.92 15.65 17.77 9.24 23.81 9.97 21.83
#> 81.1 5.1 117 139.1 159 150 106 5.2 183.1 127 78 169 81.2
#> 14.06 16.43 17.46 21.49 10.55 20.33 16.67 16.43 9.24 3.53 23.88 22.41 14.06
#> 77 43.1 91 6 24 158 69 81.3 56 164 184.2 153 136.3
#> 7.27 12.10 5.33 15.64 23.89 20.14 23.23 14.06 12.21 23.60 17.77 21.33 21.83
#> 113 128.1 180 93 18 169.1 63.1 90 30 26.1 180.1 36 42
#> 22.86 20.35 14.82 10.33 15.21 22.41 22.77 20.94 17.43 15.77 14.82 21.19 12.43
#> 25 69.1 159.1 184.3 26.2 63.2 130 26.3 45.1 86.2 188 43.2 108.1
#> 6.32 23.23 10.55 17.77 15.77 22.77 16.47 15.77 17.42 23.81 16.16 12.10 18.29
#> 197 43.3 134 188.1 184.4 37 134.1 58 57 106.1 55 123 60
#> 21.60 12.10 17.81 16.16 17.77 12.52 17.81 19.34 14.46 16.67 19.34 13.00 13.15
#> 23.1 78.1 169.2 98 62 173 122 44 198 142 1 20 162
#> 16.92 23.88 22.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 182 173.1 142.1 120 200 109 196 48.1 38 173.2 95 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 19 27 112 65 65.1 120.1 20.1 46 21 21.1 48.2 21.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 53 182.1 172 138 191 83 11 152 94 143 163 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 144 94.1 47 2 28 148 3 2.1 186.1 198.1 7 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 132 141 84.1 2.2 34 120.2 176 74 83.1 144.1 200.1 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 109.1 28.1 20.2 27.2 28.2 174 173.3 109.2 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[91]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004937073 0.210422362 0.242636682
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.18332716 0.01769987 0.80718030
#> grade_iii, Cure model
#> 1.00177200
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 69 23.23 1 25 0 1
#> 110 17.56 1 65 0 1
#> 99 21.19 1 38 0 1
#> 30 17.43 1 78 0 0
#> 13 14.34 1 54 0 1
#> 96 14.54 1 33 0 1
#> 63 22.77 1 31 1 0
#> 52 10.42 1 52 0 1
#> 99.1 21.19 1 38 0 1
#> 36 21.19 1 48 0 1
#> 29 15.45 1 68 1 0
#> 197 21.60 1 69 1 0
#> 136 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 4 17.64 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 187 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 40 18.00 1 28 1 0
#> 10 10.53 1 34 0 0
#> 15 22.68 1 48 0 0
#> 155 13.08 1 26 0 0
#> 4.1 17.64 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 134 17.81 1 47 1 0
#> 100 16.07 1 60 0 0
#> 180 14.82 1 37 0 0
#> 192 16.44 1 31 1 0
#> 76 19.22 1 54 0 1
#> 159 10.55 1 50 0 1
#> 68 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 197.1 21.60 1 69 1 0
#> 179 18.63 1 42 0 0
#> 158 20.14 1 74 1 0
#> 92 22.92 1 47 0 1
#> 105.1 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 139 21.49 1 63 1 0
#> 58 19.34 1 39 0 0
#> 18 15.21 1 49 1 0
#> 88 18.37 1 47 0 0
#> 194 22.40 1 38 0 1
#> 181 16.46 1 45 0 1
#> 183.1 9.24 1 67 1 0
#> 96.1 14.54 1 33 0 1
#> 61 10.12 1 36 0 1
#> 113 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 149 8.37 1 33 1 0
#> 130 16.47 1 53 0 1
#> 97 19.14 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 139.1 21.49 1 63 1 0
#> 179.1 18.63 1 42 0 0
#> 154 12.63 1 20 1 0
#> 195 11.76 1 NA 1 0
#> 158.1 20.14 1 74 1 0
#> 124 9.73 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 100.1 16.07 1 60 0 0
#> 197.2 21.60 1 69 1 0
#> 26 15.77 1 49 0 1
#> 175 21.91 1 43 0 0
#> 97.1 19.14 1 65 0 1
#> 15.1 22.68 1 48 0 0
#> 36.1 21.19 1 48 0 1
#> 61.1 10.12 1 36 0 1
#> 140 12.68 1 59 1 0
#> 60 13.15 1 38 1 0
#> 153 21.33 1 55 1 0
#> 14 12.89 1 21 0 0
#> 169 22.41 1 46 0 0
#> 180.1 14.82 1 37 0 0
#> 78 23.88 1 43 0 0
#> 76.1 19.22 1 54 0 1
#> 107 11.18 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 49 12.19 1 48 1 0
#> 85 16.44 1 36 0 0
#> 29.1 15.45 1 68 1 0
#> 130.1 16.47 1 53 0 1
#> 77 7.27 1 67 0 1
#> 79 16.23 1 54 1 0
#> 90 20.94 1 50 0 1
#> 153.1 21.33 1 55 1 0
#> 70 7.38 1 30 1 0
#> 41 18.02 1 40 1 0
#> 101.1 9.97 1 10 0 1
#> 79.1 16.23 1 54 1 0
#> 129 23.41 1 53 1 0
#> 5 16.43 1 51 0 1
#> 129.1 23.41 1 53 1 0
#> 106 16.67 1 49 1 0
#> 61.2 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 51 18.23 1 83 0 1
#> 56 12.21 1 60 0 0
#> 90.1 20.94 1 50 0 1
#> 91 5.33 1 61 0 1
#> 18.1 15.21 1 49 1 0
#> 111 17.45 1 47 0 1
#> 8 18.43 1 32 0 0
#> 130.2 16.47 1 53 0 1
#> 56.1 12.21 1 60 0 0
#> 96.2 14.54 1 33 0 1
#> 155.1 13.08 1 26 0 0
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 150 20.33 1 48 0 0
#> 182 24.00 0 35 0 0
#> 17 24.00 0 38 0 1
#> 182.1 24.00 0 35 0 0
#> 193 24.00 0 45 0 1
#> 53 24.00 0 32 0 1
#> 135 24.00 0 58 1 0
#> 151 24.00 0 42 0 0
#> 141 24.00 0 44 1 0
#> 17.1 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 80 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 54 24.00 0 53 1 0
#> 115 24.00 0 NA 1 0
#> 31 24.00 0 36 0 1
#> 62.1 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 143.1 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 82 24.00 0 34 0 0
#> 47 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 196.1 24.00 0 19 0 0
#> 80.1 24.00 0 41 0 0
#> 54.1 24.00 0 53 1 0
#> 7.1 24.00 0 37 1 0
#> 163 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 152.1 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 191 24.00 0 60 0 1
#> 19 24.00 0 57 0 1
#> 186 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 80.2 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 109.1 24.00 0 48 0 0
#> 151.1 24.00 0 42 0 0
#> 19.1 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 62.2 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 64.1 24.00 0 43 0 0
#> 103 24.00 0 56 1 0
#> 9.1 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 95 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 151.2 24.00 0 42 0 0
#> 156 24.00 0 50 1 0
#> 44.1 24.00 0 56 0 0
#> 74 24.00 0 43 0 1
#> 34 24.00 0 36 0 0
#> 135.1 24.00 0 58 1 0
#> 34.1 24.00 0 36 0 0
#> 7.2 24.00 0 37 1 0
#> 9.2 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 87.1 24.00 0 27 0 0
#> 67.1 24.00 0 25 0 0
#> 122 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 148 24.00 0 61 1 0
#> 73 24.00 0 NA 0 1
#> 156.1 24.00 0 50 1 0
#> 112.1 24.00 0 61 0 0
#> 115.1 24.00 0 NA 1 0
#> 67.2 24.00 0 25 0 0
#> 176.1 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 118 24.00 0 44 1 0
#> 191.1 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.18 NA NA NA
#> 2 age, Cure model 0.0177 NA NA NA
#> 3 grade_ii, Cure model 0.807 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00494 NA NA NA
#> 2 grade_ii, Survival model 0.210 NA NA NA
#> 3 grade_iii, Survival model 0.243 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1833 0.0177 0.8072 1.0018
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 248 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18332716 0.01769987 0.80718030 1.00177200
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004937073 0.210422362 0.242636682
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.027807012 0.437773432 0.176532823 0.457423815 0.705145322 0.675325079
#> [7] 0.052882187 0.847280716 0.176532823 0.176532823 0.615239195 0.114240139
#> [13] 0.105121711 0.775803220 0.283816227 0.918420195 0.887894781 0.418158750
#> [19] 0.837019163 0.061325852 0.725316058 0.928614059 0.427963683 0.565458252
#> [25] 0.655221601 0.516226032 0.312145566 0.826777014 0.246867246 0.898141576
#> [31] 0.114240139 0.350007448 0.265377825 0.036089978 0.283816227 0.595333954
#> [37] 0.140191293 0.302567269 0.635220620 0.378922554 0.087001116 0.506331900
#> [43] 0.928614059 0.675325079 0.857544010 0.044361304 0.388723289 0.948940230
#> [49] 0.477214227 0.331035617 0.140191293 0.350007448 0.765679250 0.265377825
#> [55] 0.595333954 0.565458252 0.114240139 0.585318337 0.095979367 0.331035617
#> [61] 0.061325852 0.176532823 0.857544010 0.755539441 0.715232329 0.158299147
#> [67] 0.745410195 0.077971031 0.655221601 0.003859157 0.312145566 0.816535401
#> [73] 0.806300803 0.516226032 0.615239195 0.477214227 0.969358745 0.545775455
#> [79] 0.210929574 0.158299147 0.959152980 0.408336589 0.898141576 0.545775455
#> [85] 0.013289314 0.535863436 0.013289314 0.467315769 0.857544010 0.979573585
#> [91] 0.398511362 0.785968240 0.210929574 0.989783797 0.635220620 0.447599768
#> [97] 0.369174045 0.477214227 0.785968240 0.675325079 0.725316058 0.228900211
#> [103] 0.228900211 0.256087233 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 69 110 99 30 13 96 63 52 99.1 36 29 197 136
#> 23.23 17.56 21.19 17.43 14.34 14.54 22.77 10.42 21.19 21.19 15.45 21.60 21.83
#> 177 105 187 145 40 10 15 155 183 134 100 180 192
#> 12.53 19.75 9.92 10.07 18.00 10.53 22.68 13.08 9.24 17.81 16.07 14.82 16.44
#> 76 159 68 101 197.1 179 158 92 105.1 167 139 58 18
#> 19.22 10.55 20.62 9.97 21.60 18.63 20.14 22.92 19.75 15.55 21.49 19.34 15.21
#> 88 194 181 183.1 96.1 61 113 108 149 130 97 139.1 179.1
#> 18.37 22.40 16.46 9.24 14.54 10.12 22.86 18.29 8.37 16.47 19.14 21.49 18.63
#> 154 158.1 167.1 100.1 197.2 26 175 97.1 15.1 36.1 61.1 140 60
#> 12.63 20.14 15.55 16.07 21.60 15.77 21.91 19.14 22.68 21.19 10.12 12.68 13.15
#> 153 14 169 180.1 78 76.1 107 49 85 29.1 130.1 77 79
#> 21.33 12.89 22.41 14.82 23.88 19.22 11.18 12.19 16.44 15.45 16.47 7.27 16.23
#> 90 153.1 70 41 101.1 79.1 129 5 129.1 106 61.2 25 51
#> 20.94 21.33 7.38 18.02 9.97 16.23 23.41 16.43 23.41 16.67 10.12 6.32 18.23
#> 56 90.1 91 18.1 111 8 130.2 56.1 96.2 155.1 190 190.1 150
#> 12.21 20.94 5.33 15.21 17.45 18.43 16.47 12.21 14.54 13.08 20.81 20.81 20.33
#> 182 17 182.1 193 53 135 151 141 17.1 64 80 109 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 152 44 54 31 62.1 138 143.1 7 82 47 196 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 80.1 54.1 7.1 163 174 152.1 1 191 19 186 71 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.2 112 109.1 151.1 19.1 38 67 144 62.2 176 9 142 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 9.1 119 95 173 87 162 185 151.2 156 44.1 74 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 34.1 7.2 9.2 84 87.1 67.1 122 198 148 156.1 112.1 67.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 46 137 27 2 118 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[92]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003708157 0.180493514 0.240673211
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91893832 0.01413827 0.48726077
#> grade_iii, Cure model
#> 0.88282926
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 154 12.63 1 20 1 0
#> 157 15.10 1 47 0 0
#> 18 15.21 1 49 1 0
#> 78 23.88 1 43 0 0
#> 40 18.00 1 28 1 0
#> 107 11.18 1 54 1 0
#> 164 23.60 1 76 0 1
#> 23 16.92 1 61 0 0
#> 170 19.54 1 43 0 1
#> 32 20.90 1 37 1 0
#> 195.1 11.76 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 88 18.37 1 47 0 0
#> 41 18.02 1 40 1 0
#> 179 18.63 1 42 0 0
#> 177 12.53 1 75 0 0
#> 63 22.77 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 189 10.51 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 70 7.38 1 30 1 0
#> 29 15.45 1 68 1 0
#> 199 19.81 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 15 22.68 1 48 0 0
#> 42 12.43 1 49 0 1
#> 56 12.21 1 60 0 0
#> 14 12.89 1 21 0 0
#> 136 21.83 1 43 0 1
#> 59.1 10.16 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 36 21.19 1 48 0 1
#> 77 7.27 1 67 0 1
#> 133 14.65 1 57 0 0
#> 32.1 20.90 1 37 1 0
#> 133.1 14.65 1 57 0 0
#> 96.1 14.54 1 33 0 1
#> 15.2 22.68 1 48 0 0
#> 14.1 12.89 1 21 0 0
#> 197 21.60 1 69 1 0
#> 16 8.71 1 71 0 1
#> 153 21.33 1 55 1 0
#> 42.1 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 179.1 18.63 1 42 0 0
#> 76 19.22 1 54 0 1
#> 57 14.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 175 21.91 1 43 0 0
#> 181 16.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 181.1 16.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 56.1 12.21 1 60 0 0
#> 117 17.46 1 26 0 1
#> 45 17.42 1 54 0 1
#> 45.1 17.42 1 54 0 1
#> 23.1 16.92 1 61 0 0
#> 61 10.12 1 36 0 1
#> 114 13.68 1 NA 0 0
#> 179.2 18.63 1 42 0 0
#> 61.1 10.12 1 36 0 1
#> 154.1 12.63 1 20 1 0
#> 63.1 22.77 1 31 1 0
#> 101 9.97 1 10 0 1
#> 105 19.75 1 60 0 0
#> 187 9.92 1 39 1 0
#> 49 12.19 1 48 1 0
#> 58.1 19.34 1 39 0 0
#> 26 15.77 1 49 0 1
#> 158 20.14 1 74 1 0
#> 79 16.23 1 54 1 0
#> 63.2 22.77 1 31 1 0
#> 88.1 18.37 1 47 0 0
#> 55 19.34 1 69 0 1
#> 130.1 16.47 1 53 0 1
#> 167 15.55 1 56 1 0
#> 171 16.57 1 41 0 1
#> 139.1 21.49 1 63 1 0
#> 133.2 14.65 1 57 0 0
#> 179.3 18.63 1 42 0 0
#> 140 12.68 1 59 1 0
#> 42.2 12.43 1 49 0 1
#> 136.1 21.83 1 43 0 1
#> 86 23.81 1 58 0 1
#> 76.1 19.22 1 54 0 1
#> 92 22.92 1 47 0 1
#> 129.1 23.41 1 53 1 0
#> 181.2 16.46 1 45 0 1
#> 92.1 22.92 1 47 0 1
#> 59.2 10.16 1 NA 1 0
#> 41.1 18.02 1 40 1 0
#> 79.1 16.23 1 54 1 0
#> 25 6.32 1 34 1 0
#> 117.1 17.46 1 26 0 1
#> 78.1 23.88 1 43 0 0
#> 81 14.06 1 34 0 0
#> 78.2 23.88 1 43 0 0
#> 6 15.64 1 39 0 0
#> 128 20.35 1 35 0 1
#> 93 10.33 1 52 0 1
#> 90 20.94 1 50 0 1
#> 85 16.44 1 36 0 0
#> 50.1 10.02 1 NA 1 0
#> 117.2 17.46 1 26 0 1
#> 9 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 131 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 176 24.00 0 43 0 1
#> 152.1 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 67 24.00 0 25 0 0
#> 182 24.00 0 35 0 0
#> 143 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 83 24.00 0 6 0 0
#> 53 24.00 0 32 0 1
#> 186 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 54 24.00 0 53 1 0
#> 196.1 24.00 0 19 0 0
#> 141 24.00 0 44 1 0
#> 176.1 24.00 0 43 0 1
#> 83.1 24.00 0 6 0 0
#> 2 24.00 0 9 0 0
#> 31 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 2.1 24.00 0 9 0 0
#> 196.2 24.00 0 19 0 0
#> 75 24.00 0 21 1 0
#> 75.1 24.00 0 21 1 0
#> 142.1 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 82.1 24.00 0 34 0 0
#> 146 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 152.2 24.00 0 36 0 1
#> 118 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 112.2 24.00 0 61 0 0
#> 67.1 24.00 0 25 0 0
#> 147 24.00 0 76 1 0
#> 27 24.00 0 63 1 0
#> 182.1 24.00 0 35 0 0
#> 54.1 24.00 0 53 1 0
#> 112.3 24.00 0 61 0 0
#> 67.2 24.00 0 25 0 0
#> 143.2 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 72 24.00 0 40 0 1
#> 27.1 24.00 0 63 1 0
#> 31.1 24.00 0 36 0 1
#> 74 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 109 24.00 0 48 0 0
#> 46 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 112.4 24.00 0 61 0 0
#> 200 24.00 0 64 0 0
#> 95.1 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 54.2 24.00 0 53 1 0
#> 28 24.00 0 67 1 0
#> 82.2 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#> 2.2 24.00 0 9 0 0
#> 121 24.00 0 57 1 0
#> 142.2 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 196.3 24.00 0 19 0 0
#> 94 24.00 0 51 0 1
#> 19.1 24.00 0 57 0 1
#> 33.1 24.00 0 53 0 0
#> 182.2 24.00 0 35 0 0
#> 115 24.00 0 NA 1 0
#> 84 24.00 0 39 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.919 NA NA NA
#> 2 age, Cure model 0.0141 NA NA NA
#> 3 grade_ii, Cure model 0.487 NA NA NA
#> 4 grade_iii, Cure model 0.883 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00371 NA NA NA
#> 2 grade_ii, Survival model 0.180 NA NA NA
#> 3 grade_iii, Survival model 0.241 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91894 0.01414 0.48726 0.88283
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 248.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91893832 0.01413827 0.48726077 0.88282926
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003708157 0.180493514 0.240673211
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.27018898 0.79486694 0.68239365 0.67218346 0.01042652 0.44992498
#> [7] 0.89725537 0.04453409 0.52030164 0.31035794 0.25058705 0.05549827
#> [13] 0.40926085 0.42960855 0.36988257 0.81528679 0.10539978 0.07545183
#> [19] 0.96921251 0.66197347 0.48997037 0.72313493 0.13273093 0.83590311
#> [25] 0.86638599 0.76409365 0.17117062 0.13273093 0.23049219 0.97947643
#> [31] 0.69262833 0.25058705 0.69262833 0.72313493 0.13273093 0.76409365
#> [37] 0.19066363 0.95894078 0.22040446 0.83590311 0.55083026 0.36988257
#> [43] 0.34995605 0.74354585 0.82559299 0.16103028 0.57106475 0.20071126
#> [49] 0.57106475 0.32042798 0.86638599 0.46018188 0.50016114 0.50016114
#> [55] 0.52030164 0.91791366 0.36988257 0.91791366 0.79486694 0.10539978
#> [61] 0.93839820 0.30026021 0.94867152 0.88692567 0.32042798 0.63140646
#> [67] 0.29022979 0.61120463 0.10539978 0.40926085 0.32042798 0.55083026
#> [73] 0.65177436 0.54060129 0.20071126 0.69262833 0.36988257 0.78456070
#> [79] 0.83590311 0.17117062 0.03369060 0.34995605 0.08595756 0.05549827
#> [85] 0.57106475 0.08595756 0.42960855 0.61120463 0.98974119 0.46018188
#> [91] 0.01042652 0.75381146 0.01042652 0.64157952 0.28023037 0.90758740
#> [97] 0.24055151 0.60102551 0.46018188 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 68 154 157 18 78 40 107 164 23 170 32 129 88
#> 20.62 12.63 15.10 15.21 23.88 18.00 11.18 23.60 16.92 19.54 20.90 23.41 18.37
#> 41 179 177 63 69 70 29 30 96 15 42 56 14
#> 18.02 18.63 12.53 22.77 23.23 7.38 15.45 17.43 14.54 22.68 12.43 12.21 12.89
#> 136 15.1 36 77 133 32.1 133.1 96.1 15.2 14.1 197 16 153
#> 21.83 22.68 21.19 7.27 14.65 20.90 14.65 14.54 22.68 12.89 21.60 8.71 21.33
#> 42.1 130 179.1 76 57 37 175 181 139 181.1 58 56.1 117
#> 12.43 16.47 18.63 19.22 14.46 12.52 21.91 16.46 21.49 16.46 19.34 12.21 17.46
#> 45 45.1 23.1 61 179.2 61.1 154.1 63.1 101 105 187 49 58.1
#> 17.42 17.42 16.92 10.12 18.63 10.12 12.63 22.77 9.97 19.75 9.92 12.19 19.34
#> 26 158 79 63.2 88.1 55 130.1 167 171 139.1 133.2 179.3 140
#> 15.77 20.14 16.23 22.77 18.37 19.34 16.47 15.55 16.57 21.49 14.65 18.63 12.68
#> 42.2 136.1 86 76.1 92 129.1 181.2 92.1 41.1 79.1 25 117.1 78.1
#> 12.43 21.83 23.81 19.22 22.92 23.41 16.46 22.92 18.02 16.23 6.32 17.46 23.88
#> 81 78.2 6 128 93 90 85 117.2 9 152 131 19 142
#> 14.06 23.88 15.64 20.35 10.33 20.94 16.44 17.46 24.00 24.00 24.00 24.00 24.00
#> 126 112 176 152.1 103 67 182 143 196 83 53 186 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 162 112.1 54 196.1 141 176.1 83.1 2 31 47 185 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.2 75 75.1 142.1 172 82 82.1 146 47.1 33 98 152.2 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 112.2 67.1 147 27 182.1 54.1 112.3 67.2 143.2 80 21 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 72 27.1 31.1 74 193 109 46 165 62 160 193.1 112.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 95.1 1 54.2 28 82.2 174 2.2 121 142.2 161 196.3 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 33.1 182.2 84
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[93]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00507861 0.74766718 0.44836402
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.147828958 0.004942193 -0.475345817
#> grade_iii, Cure model
#> 0.964302980
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 93 10.33 1 52 0 1
#> 36 21.19 1 48 0 1
#> 96 14.54 1 33 0 1
#> 23 16.92 1 61 0 0
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 10 10.53 1 34 0 0
#> 177 12.53 1 75 0 0
#> 177.1 12.53 1 75 0 0
#> 15 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 136 21.83 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 139 21.49 1 63 1 0
#> 10.1 10.53 1 34 0 0
#> 86 23.81 1 58 0 1
#> 10.2 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 167.1 15.55 1 56 1 0
#> 23.1 16.92 1 61 0 0
#> 195 11.76 1 NA 1 0
#> 167.2 15.55 1 56 1 0
#> 92 22.92 1 47 0 1
#> 184 17.77 1 38 0 0
#> 56 12.21 1 60 0 0
#> 70 7.38 1 30 1 0
#> 66 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 171 16.57 1 41 0 1
#> 40 18.00 1 28 1 0
#> 29 15.45 1 68 1 0
#> 45 17.42 1 54 0 1
#> 26 15.77 1 49 0 1
#> 61 10.12 1 36 0 1
#> 145 10.07 1 65 1 0
#> 40.1 18.00 1 28 1 0
#> 25 6.32 1 34 1 0
#> 179 18.63 1 42 0 0
#> 77 7.27 1 67 0 1
#> 168 23.72 1 70 0 0
#> 188 16.16 1 46 0 1
#> 125 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 43 12.10 1 61 0 1
#> 110 17.56 1 65 0 1
#> 15.1 22.68 1 48 0 0
#> 100 16.07 1 60 0 0
#> 180 14.82 1 37 0 0
#> 154 12.63 1 20 1 0
#> 25.1 6.32 1 34 1 0
#> 24 23.89 1 38 0 0
#> 179.1 18.63 1 42 0 0
#> 114 13.68 1 NA 0 0
#> 26.1 15.77 1 49 0 1
#> 181 16.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 26.2 15.77 1 49 0 1
#> 136.1 21.83 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 24.1 23.89 1 38 0 0
#> 159 10.55 1 50 0 1
#> 85 16.44 1 36 0 0
#> 59.1 10.16 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 40.2 18.00 1 28 1 0
#> 171.1 16.57 1 41 0 1
#> 155 13.08 1 26 0 0
#> 43.1 12.10 1 61 0 1
#> 111 17.45 1 47 0 1
#> 170.1 19.54 1 43 0 1
#> 101.1 9.97 1 10 0 1
#> 30 17.43 1 78 0 0
#> 129 23.41 1 53 1 0
#> 97 19.14 1 65 0 1
#> 24.2 23.89 1 38 0 0
#> 167.3 15.55 1 56 1 0
#> 100.1 16.07 1 60 0 0
#> 6.1 15.64 1 39 0 0
#> 51 18.23 1 83 0 1
#> 6.2 15.64 1 39 0 0
#> 188.1 16.16 1 46 0 1
#> 106 16.67 1 49 1 0
#> 164 23.60 1 76 0 1
#> 41 18.02 1 40 1 0
#> 179.2 18.63 1 42 0 0
#> 32 20.90 1 37 1 0
#> 5 16.43 1 51 0 1
#> 189.1 10.51 1 NA 1 0
#> 171.2 16.57 1 41 0 1
#> 199 19.81 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 61.2 10.12 1 36 0 1
#> 168.1 23.72 1 70 0 0
#> 136.2 21.83 1 43 0 1
#> 136.3 21.83 1 43 0 1
#> 183 9.24 1 67 1 0
#> 139.1 21.49 1 63 1 0
#> 105 19.75 1 60 0 0
#> 59.2 10.16 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 136.4 21.83 1 43 0 1
#> 164.1 23.60 1 76 0 1
#> 77.1 7.27 1 67 0 1
#> 183.1 9.24 1 67 1 0
#> 59.3 10.16 1 NA 1 0
#> 25.2 6.32 1 34 1 0
#> 123 13.00 1 44 1 0
#> 41.1 18.02 1 40 1 0
#> 53 24.00 0 32 0 1
#> 102 24.00 0 49 0 0
#> 131 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 135 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 54 24.00 0 53 1 0
#> 31 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 132 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 138.1 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 118.1 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 109 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 161 24.00 0 45 0 0
#> 82.1 24.00 0 34 0 0
#> 19 24.00 0 57 0 1
#> 98.2 24.00 0 34 1 0
#> 146 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 131.1 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 152 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 72 24.00 0 40 0 1
#> 28 24.00 0 67 1 0
#> 160 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 48 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 132.1 24.00 0 55 0 0
#> 176 24.00 0 43 0 1
#> 174 24.00 0 49 1 0
#> 53.1 24.00 0 32 0 1
#> 12.1 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 178.2 24.00 0 52 1 0
#> 65.1 24.00 0 57 1 0
#> 98.3 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 33 24.00 0 53 0 0
#> 135.1 24.00 0 58 1 0
#> 48.2 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 102.1 24.00 0 49 0 0
#> 98.4 24.00 0 34 1 0
#> 118.2 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 7 24.00 0 37 1 0
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 116.1 24.00 0 58 0 1
#> 44 24.00 0 56 0 0
#> 109.1 24.00 0 48 0 0
#> 152.1 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 148.1 24.00 0 61 1 0
#> 28.1 24.00 0 67 1 0
#> 1 24.00 0 23 1 0
#> 163 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 34 24.00 0 36 0 0
#> 87.1 24.00 0 27 0 0
#> 148.2 24.00 0 61 1 0
#> 174.1 24.00 0 49 1 0
#> 148.3 24.00 0 61 1 0
#> 143.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.148 NA NA NA
#> 2 age, Cure model 0.00494 NA NA NA
#> 3 grade_ii, Cure model -0.475 NA NA NA
#> 4 grade_iii, Cure model 0.964 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00508 NA NA NA
#> 2 grade_ii, Survival model 0.748 NA NA NA
#> 3 grade_iii, Survival model 0.448 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.147829 0.004942 -0.475346 0.964303
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 243.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.147828958 0.004942193 -0.475345817 0.964302980
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00507861 0.74766718 0.44836402
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.64558486 0.85760511 0.27319288 0.73531621 0.48633940 0.14925367
#> [7] 0.03987623 0.83163415 0.77061570 0.77061570 0.16155627 0.31615828
#> [13] 0.19886612 0.67316559 0.25162281 0.83163415 0.05410410 0.83163415
#> [19] 0.90062266 0.67316559 0.48633940 0.67316559 0.13607870 0.43803329
#> [25] 0.79681761 0.94278103 0.18600468 0.93439774 0.51526844 0.40970338
#> [31] 0.70855581 0.47669306 0.60876590 0.86633297 0.89202000 0.40970338
#> [37] 0.96764453 0.34752466 0.95110411 0.06775882 0.57150955 0.63632931
#> [43] 0.71751759 0.78808870 0.80557171 0.44772532 0.16155627 0.59006047
#> [49] 0.72640756 0.76189213 0.96764453 0.01185694 0.34752466 0.60876590
#> [55] 0.54319286 0.60876590 0.19886612 0.01185694 0.82292904 0.55262479
#> [61] 0.86633297 0.40970338 0.51526844 0.74419000 0.80557171 0.45739109
#> [67] 0.31615828 0.90062266 0.46700945 0.12260063 0.33698614 0.01185694
#> [73] 0.67316559 0.59006047 0.64558486 0.37872142 0.64558486 0.57150955
#> [79] 0.50564280 0.09540353 0.38941152 0.34752466 0.28409996 0.56208370
#> [85] 0.51526844 0.29470175 0.86633297 0.06775882 0.19886612 0.19886612
#> [91] 0.91758834 0.25162281 0.30538050 0.99186830 0.19886612 0.09540353
#> [97] 0.95110411 0.91758834 0.96764453 0.75307691 0.38941152 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 6 93 36 96 23 63 78 10 177 177.1 15 170 136
#> 15.64 10.33 21.19 14.54 16.92 22.77 23.88 10.53 12.53 12.53 22.68 19.54 21.83
#> 167 139 10.1 86 10.2 101 167.1 23.1 167.2 92 184 56 70
#> 15.55 21.49 10.53 23.81 10.53 9.97 15.55 16.92 15.55 22.92 17.77 12.21 7.38
#> 66 149 171 40 29 45 26 61 145 40.1 25 179 77
#> 22.13 8.37 16.57 18.00 15.45 17.42 15.77 10.12 10.07 18.00 6.32 18.63 7.27
#> 168 188 125 18 37 43 110 15.1 100 180 154 25.1 24
#> 23.72 16.16 15.65 15.21 12.52 12.10 17.56 22.68 16.07 14.82 12.63 6.32 23.89
#> 179.1 26.1 181 26.2 136.1 24.1 159 85 61.1 40.2 171.1 155 43.1
#> 18.63 15.77 16.46 15.77 21.83 23.89 10.55 16.44 10.12 18.00 16.57 13.08 12.10
#> 111 170.1 101.1 30 129 97 24.2 167.3 100.1 6.1 51 6.2 188.1
#> 17.45 19.54 9.97 17.43 23.41 19.14 23.89 15.55 16.07 15.64 18.23 15.64 16.16
#> 106 164 41 179.2 32 5 171.2 68 61.2 168.1 136.2 136.3 183
#> 16.67 23.60 18.02 18.63 20.90 16.43 16.57 20.62 10.12 23.72 21.83 21.83 9.24
#> 139.1 105 127 136.4 164.1 77.1 183.1 25.2 123 41.1 53 102 131
#> 21.49 19.75 3.53 21.83 23.60 7.27 9.24 6.32 13.00 18.02 24.00 24.00 24.00
#> 62 178 191 135 65 118 17 98 54 31 3 22 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 82 132 75 185 138 12 138.1 27 118.1 98.1 109 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 161 82.1 19 98.2 146 137 131.1 64 152 72 28 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 48 48.1 22.1 132.1 176 174 53.1 12.1 143 178.2 65.1 98.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 33 135.1 48.2 47 102.1 98.4 118.2 38 80 33.1 20 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 200 116.1 44 109.1 152.1 148 148.1 28.1 1 163 84 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 148.2 174.1 148.3 143.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[94]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0000270907 0.8085793316 0.4767010185
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.99830419 0.01386237 0.54493989
#> grade_iii, Cure model
#> 1.13948826
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 189 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 140 12.68 1 59 1 0
#> 111 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 117 17.46 1 26 0 1
#> 164 23.60 1 76 0 1
#> 40 18.00 1 28 1 0
#> 100 16.07 1 60 0 0
#> 85 16.44 1 36 0 0
#> 39 15.59 1 37 0 1
#> 66 22.13 1 53 0 0
#> 69 23.23 1 25 0 1
#> 184 17.77 1 38 0 0
#> 127 3.53 1 62 0 1
#> 30 17.43 1 78 0 0
#> 93 10.33 1 52 0 1
#> 68 20.62 1 44 0 0
#> 123 13.00 1 44 1 0
#> 24 23.89 1 38 0 0
#> 157 15.10 1 47 0 0
#> 192 16.44 1 31 1 0
#> 90 20.94 1 50 0 1
#> 183 9.24 1 67 1 0
#> 180 14.82 1 37 0 0
#> 167 15.55 1 56 1 0
#> 158 20.14 1 74 1 0
#> 192.1 16.44 1 31 1 0
#> 13 14.34 1 54 0 1
#> 167.1 15.55 1 56 1 0
#> 123.1 13.00 1 44 1 0
#> 194 22.40 1 38 0 1
#> 51 18.23 1 83 0 1
#> 37 12.52 1 57 1 0
#> 63 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 149 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 51.1 18.23 1 83 0 1
#> 111.1 17.45 1 47 0 1
#> 124 9.73 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 192.2 16.44 1 31 1 0
#> 76 19.22 1 54 0 1
#> 37.1 12.52 1 57 1 0
#> 52 10.42 1 52 0 1
#> 68.1 20.62 1 44 0 0
#> 127.1 3.53 1 62 0 1
#> 97 19.14 1 65 0 1
#> 85.2 16.44 1 36 0 0
#> 63.1 22.77 1 31 1 0
#> 70 7.38 1 30 1 0
#> 69.1 23.23 1 25 0 1
#> 61 10.12 1 36 0 1
#> 93.1 10.33 1 52 0 1
#> 168 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 57 14.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 110 17.56 1 65 0 1
#> 70.1 7.38 1 30 1 0
#> 125 15.65 1 67 1 0
#> 41 18.02 1 40 1 0
#> 190 20.81 1 42 1 0
#> 140.1 12.68 1 59 1 0
#> 55 19.34 1 69 0 1
#> 171 16.57 1 41 0 1
#> 123.2 13.00 1 44 1 0
#> 168.1 23.72 1 70 0 0
#> 171.1 16.57 1 41 0 1
#> 89 11.44 1 NA 0 0
#> 113.1 22.86 1 34 0 0
#> 69.2 23.23 1 25 0 1
#> 52.1 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 113.2 22.86 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 168.2 23.72 1 70 0 0
#> 155 13.08 1 26 0 0
#> 183.1 9.24 1 67 1 0
#> 26 15.77 1 49 0 1
#> 133.1 14.65 1 57 0 0
#> 26.1 15.77 1 49 0 1
#> 79 16.23 1 54 1 0
#> 63.2 22.77 1 31 1 0
#> 158.1 20.14 1 74 1 0
#> 117.1 17.46 1 26 0 1
#> 184.1 17.77 1 38 0 0
#> 124.1 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 153 21.33 1 55 1 0
#> 167.2 15.55 1 56 1 0
#> 29 15.45 1 68 1 0
#> 66.1 22.13 1 53 0 0
#> 70.2 7.38 1 30 1 0
#> 154 12.63 1 20 1 0
#> 190.1 20.81 1 42 1 0
#> 170 19.54 1 43 0 1
#> 97.1 19.14 1 65 0 1
#> 25 6.32 1 34 1 0
#> 99 21.19 1 38 0 1
#> 93.2 10.33 1 52 0 1
#> 188 16.16 1 46 0 1
#> 99.1 21.19 1 38 0 1
#> 194.1 22.40 1 38 0 1
#> 187 9.92 1 39 1 0
#> 5 16.43 1 51 0 1
#> 97.2 19.14 1 65 0 1
#> 42.1 12.43 1 49 0 1
#> 192.3 16.44 1 31 1 0
#> 21 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 44 24.00 0 56 0 0
#> 1 24.00 0 23 1 0
#> 144 24.00 0 28 0 1
#> 121 24.00 0 57 1 0
#> 28.1 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 84 24.00 0 39 0 1
#> 21.1 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 1.1 24.00 0 23 1 0
#> 1.2 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 185.1 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 17.1 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 122 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 9 24.00 0 31 1 0
#> 17.2 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 62 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 144.1 24.00 0 28 0 1
#> 95 24.00 0 68 0 1
#> 80.1 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 44.2 24.00 0 56 0 0
#> 176 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 143.1 24.00 0 51 0 0
#> 48.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 185.2 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 12 24.00 0 63 0 0
#> 82 24.00 0 34 0 0
#> 132.1 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 142 24.00 0 53 0 0
#> 82.1 24.00 0 34 0 0
#> 148 24.00 0 61 1 0
#> 84.1 24.00 0 39 0 1
#> 3.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 148.1 24.00 0 61 1 0
#> 1.3 24.00 0 23 1 0
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 112 24.00 0 61 0 0
#> 182 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 95.1 24.00 0 68 0 1
#> 165.1 24.00 0 47 0 0
#> 44.3 24.00 0 56 0 0
#> 31 24.00 0 36 0 1
#> 74.1 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 17.3 24.00 0 38 0 1
#> 144.2 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 7.1 24.00 0 37 1 0
#> 82.2 24.00 0 34 0 0
#> 35.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.998 NA NA NA
#> 2 age, Cure model 0.0139 NA NA NA
#> 3 grade_ii, Cure model 0.545 NA NA NA
#> 4 grade_iii, Cure model 1.14 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0000271 NA NA NA
#> 2 grade_ii, Survival model 0.809 NA NA NA
#> 3 grade_iii, Survival model 0.477 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99830 0.01386 0.54494 1.13949
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 255.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99830419 0.01386237 0.54493989 1.13948826
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0000270907 0.8085793316 0.4767010185
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.05780247 0.30778370 0.85935309 0.61552387 0.89022725 0.59959354
#> [7] 0.14491618 0.56689303 0.72584145 0.65455234 0.75400736 0.34386793
#> [13] 0.18506130 0.57511498 0.98900739 0.63120717 0.92024996 0.45090914
#> [19] 0.84034152 0.02124245 0.78753049 0.65455234 0.41108837 0.94960091
#> [25] 0.79416723 0.76094401 0.47025079 0.65455234 0.82062669 0.76094401
#> [31] 0.84034152 0.32034261 0.54158690 0.87805817 0.27162547 0.36739618
#> [37] 0.96107572 0.82719825 0.65455234 0.54158690 0.61552387 0.41108837
#> [43] 0.65455234 0.50691923 0.87805817 0.90832595 0.45090914 0.98900739
#> [49] 0.51590308 0.65455234 0.27162547 0.96678785 0.18506130 0.93787022
#> [55] 0.92024996 0.08482461 0.90229592 0.81402295 0.22832717 0.59144185
#> [61] 0.96678785 0.74703162 0.55852013 0.43156861 0.85935309 0.49783747
#> [67] 0.63909835 0.84034152 0.08482461 0.63909835 0.22832717 0.18506130
#> [73] 0.90832595 0.80080402 0.22832717 0.08482461 0.83376987 0.94960091
#> [79] 0.73298330 0.80080402 0.73298330 0.71151451 0.27162547 0.47025079
#> [85] 0.59959354 0.57511498 0.16647947 0.37889073 0.76094401 0.78089382
#> [91] 0.34386793 0.96678785 0.87184515 0.43156861 0.48865391 0.51590308
#> [97] 0.98345812 0.38996816 0.92024996 0.71869971 0.38996816 0.32034261
#> [103] 0.94375821 0.70423809 0.51590308 0.89022725 0.65455234 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 86 15 140 111 42 117 164 40 100 85 39 66 69
#> 23.81 22.68 12.68 17.45 12.43 17.46 23.60 18.00 16.07 16.44 15.59 22.13 23.23
#> 184 127 30 93 68 123 24 157 192 90 183 180 167
#> 17.77 3.53 17.43 10.33 20.62 13.00 23.89 15.10 16.44 20.94 9.24 14.82 15.55
#> 158 192.1 13 167.1 123.1 194 51 37 63 139 149 81 85.1
#> 20.14 16.44 14.34 15.55 13.00 22.40 18.23 12.52 22.77 21.49 8.37 14.06 16.44
#> 51.1 111.1 90.1 192.2 76 37.1 52 68.1 127.1 97 85.2 63.1 70
#> 18.23 17.45 20.94 16.44 19.22 12.52 10.42 20.62 3.53 19.14 16.44 22.77 7.38
#> 69.1 61 93.1 168 159 57 113 110 70.1 125 41 190 140.1
#> 23.23 10.12 10.33 23.72 10.55 14.46 22.86 17.56 7.38 15.65 18.02 20.81 12.68
#> 55 171 123.2 168.1 171.1 113.1 69.2 52.1 133 113.2 168.2 155 183.1
#> 19.34 16.57 13.00 23.72 16.57 22.86 23.23 10.42 14.65 22.86 23.72 13.08 9.24
#> 26 133.1 26.1 79 63.2 158.1 117.1 184.1 129 153 167.2 29 66.1
#> 15.77 14.65 15.77 16.23 22.77 20.14 17.46 17.77 23.41 21.33 15.55 15.45 22.13
#> 70.2 154 190.1 170 97.1 25 99 93.2 188 99.1 194.1 187 5
#> 7.38 12.63 20.81 19.54 19.14 6.32 21.19 10.33 16.16 21.19 22.40 9.92 16.43
#> 97.2 42.1 192.3 21 28 11 44 1 144 121 28.1 3 44.1
#> 19.14 12.43 16.44 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 21.1 72 1.1 1.2 47 17 27 185 172 48 185.1 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 17.1 163 74 2 161 122 35 163.1 147 9 17.2 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 143 144.1 95 80.1 132 193 44.2 176 22 143.1 48.1 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 186 7 185.2 119 12 82 132.1 38 142 82.1 148 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 65 104 137 191 148.1 1.3 160 174 112 182 165 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 44.3 31 74.1 131 17.3 144.2 141 54 7.1 82.2 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[95]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007074694 0.447618097 0.104561084
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.159066234 0.005411893 -0.161763187
#> grade_iii, Cure model
#> 0.603759224
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 10 10.53 1 34 0 0
#> 76 19.22 1 54 0 1
#> 18 15.21 1 49 1 0
#> 45 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 18.1 15.21 1 49 1 0
#> 52 10.42 1 52 0 1
#> 6 15.64 1 39 0 0
#> 106 16.67 1 49 1 0
#> 100 16.07 1 60 0 0
#> 68 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 190 20.81 1 42 1 0
#> 68.1 20.62 1 44 0 0
#> 26 15.77 1 49 0 1
#> 88 18.37 1 47 0 0
#> 167 15.55 1 56 1 0
#> 157 15.10 1 47 0 0
#> 100.1 16.07 1 60 0 0
#> 125 15.65 1 67 1 0
#> 50 10.02 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 91 5.33 1 61 0 1
#> 29 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 13 14.34 1 54 0 1
#> 111 17.45 1 47 0 1
#> 69 23.23 1 25 0 1
#> 111.1 17.45 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 150 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 123 13.00 1 44 1 0
#> 16 8.71 1 71 0 1
#> 8 18.43 1 32 0 0
#> 77 7.27 1 67 0 1
#> 85.1 16.44 1 36 0 0
#> 153 21.33 1 55 1 0
#> 166 19.98 1 48 0 0
#> 25 6.32 1 34 1 0
#> 77.1 7.27 1 67 0 1
#> 187 9.92 1 39 1 0
#> 166.1 19.98 1 48 0 0
#> 145 10.07 1 65 1 0
#> 49 12.19 1 48 1 0
#> 90 20.94 1 50 0 1
#> 15 22.68 1 48 0 0
#> 79.1 16.23 1 54 1 0
#> 30 17.43 1 78 0 0
#> 97 19.14 1 65 0 1
#> 6.1 15.64 1 39 0 0
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 124 9.73 1 NA 1 0
#> 77.2 7.27 1 67 0 1
#> 106.1 16.67 1 49 1 0
#> 43 12.10 1 61 0 1
#> 110 17.56 1 65 0 1
#> 10.1 10.53 1 34 0 0
#> 150.1 20.33 1 48 0 0
#> 6.2 15.64 1 39 0 0
#> 114 13.68 1 NA 0 0
#> 170 19.54 1 43 0 1
#> 125.1 15.65 1 67 1 0
#> 130.1 16.47 1 53 0 1
#> 18.2 15.21 1 49 1 0
#> 150.2 20.33 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 125.2 15.65 1 67 1 0
#> 159 10.55 1 50 0 1
#> 29.1 15.45 1 68 1 0
#> 117 17.46 1 26 0 1
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 57 14.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 111.2 17.45 1 47 0 1
#> 58 19.34 1 39 0 0
#> 125.3 15.65 1 67 1 0
#> 6.3 15.64 1 39 0 0
#> 37 12.52 1 57 1 0
#> 91.1 5.33 1 61 0 1
#> 25.1 6.32 1 34 1 0
#> 145.1 10.07 1 65 1 0
#> 41.1 18.02 1 40 1 0
#> 40 18.00 1 28 1 0
#> 16.1 8.71 1 71 0 1
#> 170.1 19.54 1 43 0 1
#> 88.1 18.37 1 47 0 0
#> 37.1 12.52 1 57 1 0
#> 155 13.08 1 26 0 0
#> 18.3 15.21 1 49 1 0
#> 128 20.35 1 35 0 1
#> 60 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 10.2 10.53 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 123.1 13.00 1 44 1 0
#> 40.1 18.00 1 28 1 0
#> 42 12.43 1 49 0 1
#> 88.2 18.37 1 47 0 0
#> 90.1 20.94 1 50 0 1
#> 6.4 15.64 1 39 0 0
#> 45.1 17.42 1 54 0 1
#> 86.1 23.81 1 58 0 1
#> 10.3 10.53 1 34 0 0
#> 180 14.82 1 37 0 0
#> 133 14.65 1 57 0 0
#> 24 23.89 1 38 0 0
#> 39 15.59 1 37 0 1
#> 186 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 173 24.00 0 19 0 1
#> 151 24.00 0 42 0 0
#> 1 24.00 0 23 1 0
#> 3 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 141.1 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 119 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 22 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 112 24.00 0 61 0 0
#> 7 24.00 0 37 1 0
#> 95 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 173.1 24.00 0 19 0 1
#> 80 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 95.1 24.00 0 68 0 1
#> 65.1 24.00 0 57 1 0
#> 103.1 24.00 0 56 1 0
#> 161 24.00 0 45 0 0
#> 138.1 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 141.2 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 196 24.00 0 19 0 0
#> 73 24.00 0 NA 0 1
#> 44 24.00 0 56 0 0
#> 11.1 24.00 0 42 0 1
#> 9 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 186.1 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 9.1 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 156.1 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 163 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 131.2 24.00 0 66 0 0
#> 95.2 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 80.1 24.00 0 41 0 0
#> 9.2 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 109 24.00 0 48 0 0
#> 65.2 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 95.3 24.00 0 68 0 1
#> 27.1 24.00 0 63 1 0
#> 80.2 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 11.2 24.00 0 42 0 1
#> 80.3 24.00 0 41 0 0
#> 138.2 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 112.1 24.00 0 61 0 0
#> 95.4 24.00 0 68 0 1
#> 9.3 24.00 0 31 1 0
#> 103.2 24.00 0 56 1 0
#> 200.2 24.00 0 64 0 0
#> 87.1 24.00 0 27 0 0
#> 82 24.00 0 34 0 0
#> 1.1 24.00 0 23 1 0
#> 17 24.00 0 38 0 1
#> 22.1 24.00 0 52 1 0
#> 73.1 24.00 0 NA 0 1
#> 146.1 24.00 0 63 1 0
#> 17.1 24.00 0 38 0 1
#> 109.1 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 82.1 24.00 0 34 0 0
#> 1.2 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 135 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.159 NA NA NA
#> 2 age, Cure model 0.00541 NA NA NA
#> 3 grade_ii, Cure model -0.162 NA NA NA
#> 4 grade_iii, Cure model 0.604 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00707 NA NA NA
#> 2 grade_ii, Survival model 0.448 NA NA NA
#> 3 grade_iii, Survival model 0.105 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.159066 0.005412 -0.161763 0.603759
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 259 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.159066234 0.005411893 -0.161763187 0.603759224
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007074694 0.447618097 0.104561084
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.85654947 0.89848928 0.39109039 0.76120954 0.56559272 0.08344074
#> [7] 0.76120954 0.92170644 0.69894497 0.58274406 0.64738968 0.26055893
#> [13] 0.93897037 0.61558778 0.24693685 0.26055893 0.66283476 0.42384391
#> [19] 0.74075361 0.78685416 0.64738968 0.67055126 0.82534659 0.98913178
#> [25] 0.74772160 0.12822014 0.81899617 0.53046535 0.14811855 0.53046535
#> [31] 0.29898594 0.63174729 0.84424821 0.95038177 0.41304991 0.96161071
#> [37] 0.61558778 0.20299199 0.33413785 0.97817818 0.96161071 0.94469436
#> [43] 0.33413785 0.92754397 0.88070565 0.21877579 0.16718920 0.63174729
#> [49] 0.55678231 0.40218379 0.69894497 0.45450884 0.59930432 0.96161071
#> [55] 0.58274406 0.88665994 0.51206066 0.89848928 0.29898594 0.69894497
#> [61] 0.35733482 0.67055126 0.59930432 0.76120954 0.29898594 0.67055126
#> [67] 0.89258601 0.74772160 0.52129017 0.80620683 0.46473471 0.81261475
#> [73] 0.18542192 0.53046535 0.37979624 0.67055126 0.69894497 0.86269136
#> [79] 0.98913178 0.97817818 0.92754397 0.46473471 0.48405656 0.95038177
#> [85] 0.35733482 0.42384391 0.86269136 0.83797073 0.76120954 0.28614257
#> [91] 0.83168374 0.50270325 0.89848928 0.84424821 0.48405656 0.87470277
#> [97] 0.42384391 0.21877579 0.69894497 0.56559272 0.08344074 0.89848928
#> [103] 0.79332414 0.79977837 0.03885629 0.73369766 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 177 10 76 18 45 86 18.1 52 6 106 100 68 101
#> 12.53 10.53 19.22 15.21 17.42 23.81 15.21 10.42 15.64 16.67 16.07 20.62 9.97
#> 85 190 68.1 26 88 167 157 100.1 125 81 91 29 129
#> 16.44 20.81 20.62 15.77 18.37 15.55 15.10 16.07 15.65 14.06 5.33 15.45 23.41
#> 13 111 69 111.1 150 79 123 16 8 77 85.1 153 166
#> 14.34 17.45 23.23 17.45 20.33 16.23 13.00 8.71 18.43 7.27 16.44 21.33 19.98
#> 25 77.1 187 166.1 145 49 90 15 79.1 30 97 6.1 51
#> 6.32 7.27 9.92 19.98 10.07 12.19 20.94 22.68 16.23 17.43 19.14 15.64 18.23
#> 130 77.2 106.1 43 110 10.1 150.1 6.2 170 125.1 130.1 18.2 150.2
#> 16.47 7.27 16.67 12.10 17.56 10.53 20.33 15.64 19.54 15.65 16.47 15.21 20.33
#> 125.2 159 29.1 117 96 41 57 169 111.2 58 125.3 6.3 37
#> 15.65 10.55 15.45 17.46 14.54 18.02 14.46 22.41 17.45 19.34 15.65 15.64 12.52
#> 91.1 25.1 145.1 41.1 40 16.1 170.1 88.1 37.1 155 18.3 128 60
#> 5.33 6.32 10.07 18.02 18.00 8.71 19.54 18.37 12.52 13.08 15.21 20.35 13.15
#> 184 10.2 123.1 40.1 42 88.2 90.1 6.4 45.1 86.1 10.3 180 133
#> 17.77 10.53 13.00 18.00 12.43 18.37 20.94 15.64 17.42 23.81 10.53 14.82 14.65
#> 24 39 186 200 173 151 1 3 138 141 65 141.1 11
#> 23.89 15.59 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 102 22 131 103 112 7 95 198 173.1 80 156 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 65.1 103.1 161 138.1 131.1 146 141.2 174 196 44 11.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 186.1 121 9.1 67 156.1 198.1 163 87 131.2 95.2 122 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 9.2 200.1 109 65.2 83 95.3 27.1 80.2 126 126.1 84 11.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.3 138.2 165 46 112.1 95.4 9.3 103.2 200.2 87.1 82 1.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 146.1 17.1 109.1 19 82.1 1.2 185 191 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[96]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01157531 0.82693776 0.69491525
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.614415327 0.011291726 0.008471872
#> grade_iii, Cure model
#> 0.985016392
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 190 20.81 1 42 1 0
#> 159 10.55 1 50 0 1
#> 166 19.98 1 48 0 0
#> 192 16.44 1 31 1 0
#> 81 14.06 1 34 0 0
#> 113 22.86 1 34 0 0
#> 92 22.92 1 47 0 1
#> 105 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 153 21.33 1 55 1 0
#> 78 23.88 1 43 0 0
#> 179 18.63 1 42 0 0
#> 76 19.22 1 54 0 1
#> 86 23.81 1 58 0 1
#> 23 16.92 1 61 0 0
#> 45 17.42 1 54 0 1
#> 61 10.12 1 36 0 1
#> 88 18.37 1 47 0 0
#> 24 23.89 1 38 0 0
#> 108 18.29 1 39 0 1
#> 26 15.77 1 49 0 1
#> 190.1 20.81 1 42 1 0
#> 30 17.43 1 78 0 0
#> 114 13.68 1 NA 0 0
#> 76.1 19.22 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 10 10.53 1 34 0 0
#> 24.1 23.89 1 38 0 0
#> 77 7.27 1 67 0 1
#> 188 16.16 1 46 0 1
#> 157 15.10 1 47 0 0
#> 183 9.24 1 67 1 0
#> 93 10.33 1 52 0 1
#> 183.1 9.24 1 67 1 0
#> 110 17.56 1 65 0 1
#> 189 10.51 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 195 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 70 7.38 1 30 1 0
#> 61.1 10.12 1 36 0 1
#> 154 12.63 1 20 1 0
#> 168 23.72 1 70 0 0
#> 183.2 9.24 1 67 1 0
#> 60 13.15 1 38 1 0
#> 42 12.43 1 49 0 1
#> 18 15.21 1 49 1 0
#> 169 22.41 1 46 0 0
#> 117.1 17.46 1 26 0 1
#> 5 16.43 1 51 0 1
#> 90 20.94 1 50 0 1
#> 117.2 17.46 1 26 0 1
#> 58 19.34 1 39 0 0
#> 166.1 19.98 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 183.3 9.24 1 67 1 0
#> 170 19.54 1 43 0 1
#> 99 21.19 1 38 0 1
#> 181 16.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 108.1 18.29 1 39 0 1
#> 194 22.40 1 38 0 1
#> 187 9.92 1 39 1 0
#> 43.1 12.10 1 61 0 1
#> 52 10.42 1 52 0 1
#> 159.1 10.55 1 50 0 1
#> 100 16.07 1 60 0 0
#> 51 18.23 1 83 0 1
#> 158 20.14 1 74 1 0
#> 157.1 15.10 1 47 0 0
#> 192.1 16.44 1 31 1 0
#> 190.2 20.81 1 42 1 0
#> 89 11.44 1 NA 0 0
#> 77.1 7.27 1 67 0 1
#> 24.2 23.89 1 38 0 0
#> 91 5.33 1 61 0 1
#> 92.1 22.92 1 47 0 1
#> 45.1 17.42 1 54 0 1
#> 158.1 20.14 1 74 1 0
#> 190.3 20.81 1 42 1 0
#> 52.1 10.42 1 52 0 1
#> 117.3 17.46 1 26 0 1
#> 26.1 15.77 1 49 0 1
#> 63 22.77 1 31 1 0
#> 13 14.34 1 54 0 1
#> 190.4 20.81 1 42 1 0
#> 105.1 19.75 1 60 0 0
#> 78.1 23.88 1 43 0 0
#> 166.2 19.98 1 48 0 0
#> 6 15.64 1 39 0 0
#> 192.2 16.44 1 31 1 0
#> 136 21.83 1 43 0 1
#> 113.1 22.86 1 34 0 0
#> 180 14.82 1 37 0 0
#> 139 21.49 1 63 1 0
#> 36 21.19 1 48 0 1
#> 108.2 18.29 1 39 0 1
#> 192.3 16.44 1 31 1 0
#> 57 14.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 106 16.67 1 49 1 0
#> 42.1 12.43 1 49 0 1
#> 37 12.52 1 57 1 0
#> 10.1 10.53 1 34 0 0
#> 123 13.00 1 44 1 0
#> 140 12.68 1 59 1 0
#> 96 14.54 1 33 0 1
#> 85 16.44 1 36 0 0
#> 81.2 14.06 1 34 0 0
#> 136.1 21.83 1 43 0 1
#> 78.2 23.88 1 43 0 0
#> 66 22.13 1 53 0 0
#> 17 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 83 24.00 0 6 0 0
#> 104 24.00 0 50 1 0
#> 21 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 146 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 17.1 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 102 24.00 0 49 0 0
#> 186 24.00 0 45 1 0
#> 38 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 118 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 132 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 176 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 64 24.00 0 43 0 0
#> 46.1 24.00 0 71 0 0
#> 173.1 24.00 0 19 0 1
#> 142.1 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 72 24.00 0 40 0 1
#> 2 24.00 0 9 0 0
#> 193 24.00 0 45 0 1
#> 2.1 24.00 0 9 0 0
#> 20 24.00 0 46 1 0
#> 73 24.00 0 NA 0 1
#> 102.1 24.00 0 49 0 0
#> 176.1 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 83.1 24.00 0 6 0 0
#> 27.1 24.00 0 63 1 0
#> 20.1 24.00 0 46 1 0
#> 119 24.00 0 17 0 0
#> 131 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 160 24.00 0 31 1 0
#> 46.2 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 142.2 24.00 0 53 0 0
#> 103.1 24.00 0 56 1 0
#> 144 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 151 24.00 0 42 0 0
#> 20.2 24.00 0 46 1 0
#> 27.2 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 75.1 24.00 0 21 1 0
#> 116 24.00 0 58 0 1
#> 2.2 24.00 0 9 0 0
#> 126.1 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 151.1 24.00 0 42 0 0
#> 54 24.00 0 53 1 0
#> 198.1 24.00 0 66 0 1
#> 67 24.00 0 25 0 0
#> 27.3 24.00 0 63 1 0
#> 12.1 24.00 0 63 0 0
#> 12.2 24.00 0 63 0 0
#> 74.1 24.00 0 43 0 1
#> 176.2 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 83.2 24.00 0 6 0 0
#> 146.2 24.00 0 63 1 0
#> 173.2 24.00 0 19 0 1
#> 193.1 24.00 0 45 0 1
#> 126.2 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.614 NA NA NA
#> 2 age, Cure model 0.0113 NA NA NA
#> 3 grade_ii, Cure model 0.00847 NA NA NA
#> 4 grade_iii, Cure model 0.985 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0116 NA NA NA
#> 2 grade_ii, Survival model 0.827 NA NA NA
#> 3 grade_iii, Survival model 0.695 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.614415 0.011292 0.008472 0.985016
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 268.1
#> Residual Deviance: 257.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.614415327 0.011291726 0.008471872 0.985016392
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01157531 0.82693776 0.69491525
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6043922 0.9383215 0.6559732 0.8116894 0.8890039 0.4397559 0.4063840
#> [8] 0.6762268 0.7614192 0.5650987 0.2453952 0.7148956 0.7025717 0.3354978
#> [15] 0.7971070 0.7871867 0.9624152 0.7270879 0.1288623 0.7331728 0.8473356
#> [22] 0.6043922 0.7820321 0.7025717 0.8890039 0.9452869 0.1288623 0.9910051
#> [29] 0.8385443 0.8643154 0.9756115 0.9590366 0.9756115 0.7559578 0.9275778
#> [36] 0.3849301 0.9879320 0.9624152 0.9126433 0.3612668 0.9756115 0.9009410
#> [43] 0.9202211 0.8601185 0.4871353 0.7614192 0.8340806 0.5950321 0.7614192
#> [50] 0.6960682 0.6559732 0.7148956 0.9756115 0.6895298 0.5756820 0.8069044
#> [57] 0.9312203 0.7331728 0.5019938 0.9723527 0.9312203 0.9522277 0.9383215
#> [64] 0.8429515 0.7503651 0.6420801 0.8643154 0.8116894 0.6043922 0.9910051
#> [71] 0.1288623 0.9970170 0.4063840 0.7871867 0.6420801 0.6043922 0.9522277
#> [78] 0.7614192 0.8473356 0.4719513 0.8849808 0.6043922 0.6762268 0.2453952
#> [85] 0.6559732 0.8558585 0.8116894 0.5296500 0.4397559 0.8726307 0.5538134
#> [92] 0.5756820 0.7331728 0.8116894 0.8809068 0.9690654 0.8020510 0.9202211
#> [99] 0.9164590 0.9452869 0.9048931 0.9087973 0.8767876 0.8116894 0.8890039
#> [106] 0.5296500 0.2453952 0.5159788 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 190 159 166 192 81 113 92 105 117 153 78 179 76
#> 20.81 10.55 19.98 16.44 14.06 22.86 22.92 19.75 17.46 21.33 23.88 18.63 19.22
#> 86 23 45 61 88 24 108 26 190.1 30 76.1 81.1 10
#> 23.81 16.92 17.42 10.12 18.37 23.89 18.29 15.77 20.81 17.43 19.22 14.06 10.53
#> 24.1 77 188 157 183 93 183.1 110 49 69 70 61.1 154
#> 23.89 7.27 16.16 15.10 9.24 10.33 9.24 17.56 12.19 23.23 7.38 10.12 12.63
#> 168 183.2 60 42 18 169 117.1 5 90 117.2 58 166.1 179.1
#> 23.72 9.24 13.15 12.43 15.21 22.41 17.46 16.43 20.94 17.46 19.34 19.98 18.63
#> 183.3 170 99 181 43 108.1 194 187 43.1 52 159.1 100 51
#> 9.24 19.54 21.19 16.46 12.10 18.29 22.40 9.92 12.10 10.42 10.55 16.07 18.23
#> 158 157.1 192.1 190.2 77.1 24.2 91 92.1 45.1 158.1 190.3 52.1 117.3
#> 20.14 15.10 16.44 20.81 7.27 23.89 5.33 22.92 17.42 20.14 20.81 10.42 17.46
#> 26.1 63 13 190.4 105.1 78.1 166.2 6 192.2 136 113.1 180 139
#> 15.77 22.77 14.34 20.81 19.75 23.88 19.98 15.64 16.44 21.83 22.86 14.82 21.49
#> 36 108.2 192.3 57 145 106 42.1 37 10.1 123 140 96 85
#> 21.19 18.29 16.44 14.46 10.07 16.67 12.43 12.52 10.53 13.00 12.68 14.54 16.44
#> 81.2 136.1 78.2 66 17 34 83 104 21 75 173 146 33
#> 14.06 21.83 23.88 22.13 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 17.1 87 102 186 38 146.1 142 74 35 27 138 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 182 118 46 98 132 126 103 176 1 64 46.1 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 82 72 2 193 2.1 20 102.1 176.1 62 83.1 27.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 131 141 3 198 160 46.2 161 142.2 103.1 144 147 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.2 27.2 137 120 75.1 116 2.2 126.1 163 121 151.1 54 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 27.3 12.1 12.2 74.1 176.2 9 185 83.2 146.2 173.2 193.1 126.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[97]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009538587 0.995222241 0.979246794
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.01146663 0.01748856 0.10173974
#> grade_iii, Cure model
#> 1.18700971
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 181 16.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 183 9.24 1 67 1 0
#> 66 22.13 1 53 0 0
#> 79 16.23 1 54 1 0
#> 58 19.34 1 39 0 0
#> 134 17.81 1 47 1 0
#> 171 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 108 18.29 1 39 0 1
#> 139 21.49 1 63 1 0
#> 110 17.56 1 65 0 1
#> 85 16.44 1 36 0 0
#> 195 11.76 1 NA 1 0
#> 139.1 21.49 1 63 1 0
#> 32 20.90 1 37 1 0
#> 128 20.35 1 35 0 1
#> 45 17.42 1 54 0 1
#> 140 12.68 1 59 1 0
#> 15 22.68 1 48 0 0
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 60 13.15 1 38 1 0
#> 130 16.47 1 53 0 1
#> 79.1 16.23 1 54 1 0
#> 187.1 9.92 1 39 1 0
#> 157 15.10 1 47 0 0
#> 66.1 22.13 1 53 0 0
#> 190 20.81 1 42 1 0
#> 32.1 20.90 1 37 1 0
#> 57 14.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 192 16.44 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 166 19.98 1 48 0 0
#> 101 9.97 1 10 0 1
#> 130.1 16.47 1 53 0 1
#> 192.1 16.44 1 31 1 0
#> 52 10.42 1 52 0 1
#> 187.2 9.92 1 39 1 0
#> 79.2 16.23 1 54 1 0
#> 133 14.65 1 57 0 0
#> 128.1 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 43 12.10 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 199.1 19.81 1 NA 0 1
#> 61 10.12 1 36 0 1
#> 149 8.37 1 33 1 0
#> 39 15.59 1 37 0 1
#> 123.1 13.00 1 44 1 0
#> 169 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 36 21.19 1 48 0 1
#> 81 14.06 1 34 0 0
#> 127 3.53 1 62 0 1
#> 91.1 5.33 1 61 0 1
#> 168 23.72 1 70 0 0
#> 93 10.33 1 52 0 1
#> 100 16.07 1 60 0 0
#> 30 17.43 1 78 0 0
#> 23 16.92 1 61 0 0
#> 124 9.73 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 15.1 22.68 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 127.1 3.53 1 62 0 1
#> 85.1 16.44 1 36 0 0
#> 39.1 15.59 1 37 0 1
#> 175 21.91 1 43 0 0
#> 157.1 15.10 1 47 0 0
#> 106 16.67 1 49 1 0
#> 101.1 9.97 1 10 0 1
#> 81.1 14.06 1 34 0 0
#> 145 10.07 1 65 1 0
#> 194 22.40 1 38 0 1
#> 91.2 5.33 1 61 0 1
#> 175.1 21.91 1 43 0 0
#> 117 17.46 1 26 0 1
#> 37 12.52 1 57 1 0
#> 51 18.23 1 83 0 1
#> 106.1 16.67 1 49 1 0
#> 199.2 19.81 1 NA 0 1
#> 23.1 16.92 1 61 0 0
#> 16 8.71 1 71 0 1
#> 108.2 18.29 1 39 0 1
#> 177 12.53 1 75 0 0
#> 195.1 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 6 15.64 1 39 0 0
#> 145.1 10.07 1 65 1 0
#> 15.2 22.68 1 48 0 0
#> 106.2 16.67 1 49 1 0
#> 127.2 3.53 1 62 0 1
#> 188.1 16.16 1 46 0 1
#> 136 21.83 1 43 0 1
#> 125.1 15.65 1 67 1 0
#> 99 21.19 1 38 0 1
#> 105.1 19.75 1 60 0 0
#> 70 7.38 1 30 1 0
#> 189 10.51 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 37.1 12.52 1 57 1 0
#> 187.3 9.92 1 39 1 0
#> 16.1 8.71 1 71 0 1
#> 85.2 16.44 1 36 0 0
#> 168.1 23.72 1 70 0 0
#> 37.2 12.52 1 57 1 0
#> 78 23.88 1 43 0 0
#> 23.2 16.92 1 61 0 0
#> 103 24.00 0 56 1 0
#> 165 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 186 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 126 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 47 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 84.1 24.00 0 39 0 1
#> 22 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 132 24.00 0 55 0 0
#> 162 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 104.1 24.00 0 50 1 0
#> 126.1 24.00 0 48 0 0
#> 160.1 24.00 0 31 1 0
#> 185.1 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 137.1 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 185.2 24.00 0 44 1 0
#> 9.1 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 132.1 24.00 0 55 0 0
#> 109 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 31 24.00 0 36 0 1
#> 112 24.00 0 61 0 0
#> 47.1 24.00 0 38 0 1
#> 160.2 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 22.1 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 9.2 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 64 24.00 0 43 0 0
#> 112.1 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 120.2 24.00 0 68 0 1
#> 112.2 24.00 0 61 0 0
#> 83 24.00 0 6 0 0
#> 87.1 24.00 0 27 0 0
#> 82 24.00 0 34 0 0
#> 160.3 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 165.1 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 27 24.00 0 63 1 0
#> 118.1 24.00 0 44 1 0
#> 138.1 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 118.2 24.00 0 44 1 0
#> 165.2 24.00 0 47 0 0
#> 19 24.00 0 57 0 1
#> 161.1 24.00 0 45 0 0
#> 163 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 122 24.00 0 66 0 0
#> 165.3 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 87.2 24.00 0 27 0 0
#> 122.1 24.00 0 66 0 0
#> 104.2 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 27.1 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 132.2 24.00 0 55 0 0
#> 109.1 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.01 NA NA NA
#> 2 age, Cure model 0.0175 NA NA NA
#> 3 grade_ii, Cure model 0.102 NA NA NA
#> 4 grade_iii, Cure model 1.19 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00954 NA NA NA
#> 2 grade_ii, Survival model 0.995 NA NA NA
#> 3 grade_iii, Survival model 0.979 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.01147 0.01749 0.10174 1.18701
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 248 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.01146663 0.01748856 0.10173974 1.18700971
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009538587 0.995222241 0.979246794
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.95336838 0.79383350 0.27443241 0.96570430 0.42851309 0.82261358
#> [7] 0.66093326 0.70649160 0.77830514 0.90133871 0.66955382 0.52408558
#> [13] 0.71326886 0.79884163 0.52408558 0.57515657 0.60658425 0.73857304
#> [19] 0.90883473 0.30652265 0.72619323 0.98349210 0.89748274 0.78365097
#> [25] 0.82261358 0.95336838 0.87384954 0.42851309 0.59641450 0.57515657
#> [31] 0.88577326 0.84923126 0.79884163 0.62508193 0.94693615 0.78365097
#> [37] 0.79884163 0.93023426 0.95336838 0.82261358 0.88180133 0.60658425
#> [43] 0.98059600 0.92675702 0.63432027 0.93706011 0.97471073 0.86585661
#> [49] 0.90133871 0.38104753 0.85352305 0.55139595 0.88969091 0.99187685
#> [55] 0.98349210 0.18957483 0.93366822 0.84486783 0.73241202 0.74456140
#> [61] 0.83612873 0.30652265 0.66955382 0.99187685 0.79884163 0.86585661
#> [67] 0.46839015 0.87384954 0.76205197 0.94693615 0.88969091 0.94041853
#> [73] 0.40672295 0.98349210 0.46839015 0.71980100 0.91621607 0.69257214
#> [79] 0.76205197 0.74456140 0.96876267 0.66955382 0.91253320 0.65226174
#> [85] 0.86174476 0.94041853 0.30652265 0.76205197 0.99187685 0.83612873
#> [91] 0.50661972 0.85352305 0.55139595 0.63432027 0.97766489 0.69257214
#> [97] 0.91621607 0.95336838 0.96876267 0.79884163 0.18957483 0.91621607
#> [103] 0.09763532 0.74456140 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 187 181 63 183 66 79 58 134 171 123 108 139 110
#> 9.92 16.46 22.77 9.24 22.13 16.23 19.34 17.81 16.57 13.00 18.29 21.49 17.56
#> 85 139.1 32 128 45 140 15 111 91 60 130 79.1 187.1
#> 16.44 21.49 20.90 20.35 17.42 12.68 22.68 17.45 5.33 13.15 16.47 16.23 9.92
#> 157 66.1 190 32.1 57 26 192 166 101 130.1 192.1 52 187.2
#> 15.10 22.13 20.81 20.90 14.46 15.77 16.44 19.98 9.97 16.47 16.44 10.42 9.92
#> 79.2 133 128.1 77 43 105 61 149 39 123.1 169 125 36
#> 16.23 14.65 20.35 7.27 12.10 19.75 10.12 8.37 15.59 13.00 22.41 15.65 21.19
#> 81 127 91.1 168 93 100 30 23 188 15.1 108.1 127.1 85.1
#> 14.06 3.53 5.33 23.72 10.33 16.07 17.43 16.92 16.16 22.68 18.29 3.53 16.44
#> 39.1 175 157.1 106 101.1 81.1 145 194 91.2 175.1 117 37 51
#> 15.59 21.91 15.10 16.67 9.97 14.06 10.07 22.40 5.33 21.91 17.46 12.52 18.23
#> 106.1 23.1 16 108.2 177 170 6 145.1 15.2 106.2 127.2 188.1 136
#> 16.67 16.92 8.71 18.29 12.53 19.54 15.64 10.07 22.68 16.67 3.53 16.16 21.83
#> 125.1 99 105.1 70 51.1 37.1 187.3 16.1 85.2 168.1 37.2 78 23.2
#> 15.65 21.19 19.75 7.38 18.23 12.52 9.92 8.71 16.44 23.72 12.52 23.88 16.92
#> 103 165 9 160 84 186 144 185 7 126 47 120 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 22 196 132 162 104 65 121 104.1 126.1 160.1 185.1 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 137 62 34 137.1 118 185.2 9.1 48 193 132.1 109 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 11 31 112 47.1 160.2 143 120.1 22.1 87 46 9.2 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 112.1 20 120.2 112.2 83 87.1 82 160.3 161 165.1 27 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 146 198 118.2 165.2 19 161.1 163 72 122 165.3 119 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.2 122.1 104.2 12 27.1 53 132.2 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[98]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00657128 0.61046616 0.61242607
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.26109353 -0.01132165 0.33576677
#> grade_iii, Cure model
#> 1.02123196
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 5 16.43 1 51 0 1
#> 134 17.81 1 47 1 0
#> 70 7.38 1 30 1 0
#> 40 18.00 1 28 1 0
#> 197 21.60 1 69 1 0
#> 111 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 179 18.63 1 42 0 0
#> 171 16.57 1 41 0 1
#> 68 20.62 1 44 0 0
#> 167 15.55 1 56 1 0
#> 117 17.46 1 26 0 1
#> 190 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 52 10.42 1 52 0 1
#> 32 20.90 1 37 1 0
#> 133 14.65 1 57 0 0
#> 136.1 21.83 1 43 0 1
#> 18 15.21 1 49 1 0
#> 150 20.33 1 48 0 0
#> 140 12.68 1 59 1 0
#> 96 14.54 1 33 0 1
#> 69 23.23 1 25 0 1
#> 24 23.89 1 38 0 0
#> 150.1 20.33 1 48 0 0
#> 97 19.14 1 65 0 1
#> 128 20.35 1 35 0 1
#> 199 19.81 1 NA 0 1
#> 79 16.23 1 54 1 0
#> 157 15.10 1 47 0 0
#> 96.1 14.54 1 33 0 1
#> 197.1 21.60 1 69 1 0
#> 15 22.68 1 48 0 0
#> 32.1 20.90 1 37 1 0
#> 110 17.56 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 188 16.16 1 46 0 1
#> 157.1 15.10 1 47 0 0
#> 166 19.98 1 48 0 0
#> 189.1 10.51 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 61 10.12 1 36 0 1
#> 155 13.08 1 26 0 0
#> 168 23.72 1 70 0 0
#> 68.1 20.62 1 44 0 0
#> 68.2 20.62 1 44 0 0
#> 57 14.46 1 45 0 1
#> 113.1 22.86 1 34 0 0
#> 150.2 20.33 1 48 0 0
#> 145 10.07 1 65 1 0
#> 13 14.34 1 54 0 1
#> 45 17.42 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 70.1 7.38 1 30 1 0
#> 145.1 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 197.2 21.60 1 69 1 0
#> 181 16.46 1 45 0 1
#> 105 19.75 1 60 0 0
#> 181.1 16.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 168.1 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 13.2 14.34 1 54 0 1
#> 123 13.00 1 44 1 0
#> 96.2 14.54 1 33 0 1
#> 89 11.44 1 NA 0 0
#> 155.1 13.08 1 26 0 0
#> 13.3 14.34 1 54 0 1
#> 110.1 17.56 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 159.1 10.55 1 50 0 1
#> 117.1 17.46 1 26 0 1
#> 92 22.92 1 47 0 1
#> 92.1 22.92 1 47 0 1
#> 177 12.53 1 75 0 0
#> 76.1 19.22 1 54 0 1
#> 184 17.77 1 38 0 0
#> 175.1 21.91 1 43 0 0
#> 93 10.33 1 52 0 1
#> 79.1 16.23 1 54 1 0
#> 158 20.14 1 74 1 0
#> 42 12.43 1 49 0 1
#> 18.1 15.21 1 49 1 0
#> 110.2 17.56 1 65 0 1
#> 42.1 12.43 1 49 0 1
#> 14 12.89 1 21 0 0
#> 90 20.94 1 50 0 1
#> 26 15.77 1 49 0 1
#> 52.1 10.42 1 52 0 1
#> 88 18.37 1 47 0 0
#> 14.1 12.89 1 21 0 0
#> 154 12.63 1 20 1 0
#> 117.2 17.46 1 26 0 1
#> 99 21.19 1 38 0 1
#> 39 15.59 1 37 0 1
#> 70.2 7.38 1 30 1 0
#> 150.3 20.33 1 48 0 0
#> 106 16.67 1 49 1 0
#> 188.1 16.16 1 46 0 1
#> 127.1 3.53 1 62 0 1
#> 181.2 16.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 42.2 12.43 1 49 0 1
#> 129 23.41 1 53 1 0
#> 52.2 10.42 1 52 0 1
#> 105.1 19.75 1 60 0 0
#> 60 13.15 1 38 1 0
#> 95 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 118 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 2 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 165 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 120 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 148 24.00 0 61 1 0
#> 163 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 53 24.00 0 32 0 1
#> 143 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 33 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 178 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 198 24.00 0 66 0 1
#> 116 24.00 0 58 0 1
#> 178.1 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 126 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 132.1 24.00 0 55 0 0
#> 196.2 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 62 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 146 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 74 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 196.3 24.00 0 19 0 0
#> 65.1 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 178.2 24.00 0 52 1 0
#> 33.1 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 120.2 24.00 0 68 0 1
#> 48 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 21.1 24.00 0 47 0 0
#> 152 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 62.1 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 53.1 24.00 0 32 0 1
#> 165.1 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 48.1 24.00 0 31 1 0
#> 120.3 24.00 0 68 0 1
#> 131.1 24.00 0 66 0 0
#> 132.2 24.00 0 55 0 0
#> 198.1 24.00 0 66 0 1
#> 17.1 24.00 0 38 0 1
#> 165.2 24.00 0 47 0 0
#> 185 24.00 0 44 1 0
#> 120.4 24.00 0 68 0 1
#> 102.1 24.00 0 49 0 0
#> 46.1 24.00 0 71 0 0
#> 47 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 152.1 24.00 0 36 0 1
#> 156.1 24.00 0 50 1 0
#> 116.1 24.00 0 58 0 1
#> 103.1 24.00 0 56 1 0
#> 131.2 24.00 0 66 0 0
#> 33.2 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.261 NA NA NA
#> 2 age, Cure model -0.0113 NA NA NA
#> 3 grade_ii, Cure model 0.336 NA NA NA
#> 4 grade_iii, Cure model 1.02 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00657 NA NA NA
#> 2 grade_ii, Survival model 0.610 NA NA NA
#> 3 grade_iii, Survival model 0.612 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.26109 -0.01132 0.33577 1.02123
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 254.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.26109353 -0.01132165 0.33576677 1.02123196
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00657128 0.61046616 0.61242607
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.593606601 0.450990088 0.951999054 0.440884884 0.179599950 0.528592943
#> [7] 0.379605131 0.410058259 0.557068132 0.260584888 0.656386263 0.500300012
#> [13] 0.250773141 0.975981182 0.157851592 0.894763729 0.231236112 0.700173646
#> [19] 0.157851592 0.665228474 0.299621973 0.827895826 0.709030083 0.069180017
#> [25] 0.005153347 0.299621973 0.399855029 0.289723866 0.602757938 0.682641636
#> [31] 0.709030083 0.179599950 0.123358554 0.231236112 0.471090769 0.101919343
#> [37] 0.620763692 0.682641636 0.348789677 0.134873542 0.927534731 0.785529383
#> [43] 0.030376609 0.260584888 0.260584888 0.734806201 0.101919343 0.299621973
#> [49] 0.935732475 0.743462547 0.538135879 0.743462547 0.951999054 0.935732475
#> [55] 0.984029125 0.179599950 0.566441921 0.359033167 0.566441921 0.430654994
#> [61] 0.030376609 0.878185993 0.743462547 0.802479998 0.709030083 0.785529383
#> [67] 0.743462547 0.471090769 0.878185993 0.500300012 0.081358488 0.081358488
#> [73] 0.844816585 0.379605131 0.461016218 0.134873542 0.919303798 0.602757938
#> [79] 0.338626943 0.853283562 0.665228474 0.471090769 0.853283562 0.810966395
#> [85] 0.220854741 0.638581564 0.894763729 0.420323100 0.810966395 0.836382500
#> [91] 0.500300012 0.210310806 0.647511249 0.951999054 0.299621973 0.547629360
#> [97] 0.620763692 0.984029125 0.566441921 0.018602531 0.853283562 0.055667508
#> [103] 0.894763729 0.359033167 0.777036799 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 5 134 70 40 197 111 76 179 171 68 167 117 190
#> 16.43 17.81 7.38 18.00 21.60 17.45 19.22 18.63 16.57 20.62 15.55 17.46 20.81
#> 77 136 52 32 133 136.1 18 150 140 96 69 24 150.1
#> 7.27 21.83 10.42 20.90 14.65 21.83 15.21 20.33 12.68 14.54 23.23 23.89 20.33
#> 97 128 79 157 96.1 197.1 15 32.1 110 113 188 157.1 166
#> 19.14 20.35 16.23 15.10 14.54 21.60 22.68 20.90 17.56 22.86 16.16 15.10 19.98
#> 175 61 155 168 68.1 68.2 57 113.1 150.2 145 13 45 13.1
#> 21.91 10.12 13.08 23.72 20.62 20.62 14.46 22.86 20.33 10.07 14.34 17.42 14.34
#> 70.1 145.1 127 197.2 181 105 181.1 41 168.1 159 13.2 123 96.2
#> 7.38 10.07 3.53 21.60 16.46 19.75 16.46 18.02 23.72 10.55 14.34 13.00 14.54
#> 155.1 13.3 110.1 159.1 117.1 92 92.1 177 76.1 184 175.1 93 79.1
#> 13.08 14.34 17.56 10.55 17.46 22.92 22.92 12.53 19.22 17.77 21.91 10.33 16.23
#> 158 42 18.1 110.2 42.1 14 90 26 52.1 88 14.1 154 117.2
#> 20.14 12.43 15.21 17.56 12.43 12.89 20.94 15.77 10.42 18.37 12.89 12.63 17.46
#> 99 39 70.2 150.3 106 188.1 127.1 181.2 86 42.2 129 52.2 105.1
#> 21.19 15.59 7.38 20.33 16.67 16.16 3.53 16.46 23.81 12.43 23.41 10.42 19.75
#> 60 95 173 118 138 196 196.1 2 151 165 35 109 11
#> 13.15 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 120.1 2.1 148 163 135 53 143 12 33 132 178 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 116 178.1 142 22 126 9 119 21 72 44 132.1 196.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 54 62 64 146 122 94 74 65 20 196.3 65.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.2 33.1 120.2 48 102 21.1 152 46 62.1 156 103 17 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 165.1 141 147 48.1 120.3 131.1 132.2 198.1 17.1 165.2 185 120.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 46.1 47 174 152.1 156.1 116.1 103.1 131.2 33.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[99]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0002975361 0.9314982360 0.6958925926
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.43552394 0.01184936 0.02002185
#> grade_iii, Cure model
#> 0.35963117
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 110 17.56 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 130 16.47 1 53 0 1
#> 108 18.29 1 39 0 1
#> 169 22.41 1 46 0 0
#> 108.1 18.29 1 39 0 1
#> 170 19.54 1 43 0 1
#> 58 19.34 1 39 0 0
#> 149 8.37 1 33 1 0
#> 99 21.19 1 38 0 1
#> 180 14.82 1 37 0 0
#> 140 12.68 1 59 1 0
#> 107 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 50.1 10.02 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 154 12.63 1 20 1 0
#> 26 15.77 1 49 0 1
#> 113 22.86 1 34 0 0
#> 15 22.68 1 48 0 0
#> 49 12.19 1 48 1 0
#> 57 14.46 1 45 0 1
#> 154.1 12.63 1 20 1 0
#> 30 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 170.1 19.54 1 43 0 1
#> 190 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 58.1 19.34 1 39 0 0
#> 24 23.89 1 38 0 0
#> 30.1 17.43 1 78 0 0
#> 111 17.45 1 47 0 1
#> 149.1 8.37 1 33 1 0
#> 30.2 17.43 1 78 0 0
#> 51 18.23 1 83 0 1
#> 194 22.40 1 38 0 1
#> 97 19.14 1 65 0 1
#> 70 7.38 1 30 1 0
#> 40 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 66 22.13 1 53 0 0
#> 157 15.10 1 47 0 0
#> 167 15.55 1 56 1 0
#> 90 20.94 1 50 0 1
#> 127 3.53 1 62 0 1
#> 66.1 22.13 1 53 0 0
#> 145 10.07 1 65 1 0
#> 57.1 14.46 1 45 0 1
#> 61.1 10.12 1 36 0 1
#> 184 17.77 1 38 0 0
#> 123 13.00 1 44 1 0
#> 129 23.41 1 53 1 0
#> 187 9.92 1 39 1 0
#> 128 20.35 1 35 0 1
#> 10 10.53 1 34 0 0
#> 149.2 8.37 1 33 1 0
#> 195 11.76 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 110.1 17.56 1 65 0 1
#> 32 20.90 1 37 1 0
#> 106 16.67 1 49 1 0
#> 136 21.83 1 43 0 1
#> 92 22.92 1 47 0 1
#> 117 17.46 1 26 0 1
#> 78 23.88 1 43 0 0
#> 42 12.43 1 49 0 1
#> 58.2 19.34 1 39 0 0
#> 59 10.16 1 NA 1 0
#> 58.3 19.34 1 39 0 0
#> 100 16.07 1 60 0 0
#> 187.1 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 45 17.42 1 54 0 1
#> 18 15.21 1 49 1 0
#> 140.1 12.68 1 59 1 0
#> 18.1 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 153 21.33 1 55 1 0
#> 128.1 20.35 1 35 0 1
#> 150 20.33 1 48 0 0
#> 57.2 14.46 1 45 0 1
#> 111.1 17.45 1 47 0 1
#> 134 17.81 1 47 1 0
#> 184.1 17.77 1 38 0 0
#> 10.2 10.53 1 34 0 0
#> 61.2 10.12 1 36 0 1
#> 39 15.59 1 37 0 1
#> 187.2 9.92 1 39 1 0
#> 41 18.02 1 40 1 0
#> 175.1 21.91 1 43 0 0
#> 8 18.43 1 32 0 0
#> 180.1 14.82 1 37 0 0
#> 24.1 23.89 1 38 0 0
#> 13 14.34 1 54 0 1
#> 29 15.45 1 68 1 0
#> 61.3 10.12 1 36 0 1
#> 166 19.98 1 48 0 0
#> 117.1 17.46 1 26 0 1
#> 45.1 17.42 1 54 0 1
#> 50.2 10.02 1 NA 1 0
#> 45.2 17.42 1 54 0 1
#> 93 10.33 1 52 0 1
#> 127.1 3.53 1 62 0 1
#> 13.1 14.34 1 54 0 1
#> 157.1 15.10 1 47 0 0
#> 166.1 19.98 1 48 0 0
#> 105 19.75 1 60 0 0
#> 192 16.44 1 31 1 0
#> 14 12.89 1 21 0 0
#> 111.2 17.45 1 47 0 1
#> 126 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 31 24.00 0 36 0 1
#> 72 24.00 0 40 0 1
#> 20 24.00 0 46 1 0
#> 87 24.00 0 27 0 0
#> 200 24.00 0 64 0 0
#> 141 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#> 142 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 152 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 21 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 161 24.00 0 45 0 0
#> 115 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 116.1 24.00 0 58 0 1
#> 71 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 82 24.00 0 34 0 0
#> 82.1 24.00 0 34 0 0
#> 115.1 24.00 0 NA 1 0
#> 71.1 24.00 0 51 0 0
#> 196.1 24.00 0 19 0 0
#> 47 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#> 3 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 94.1 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 12 24.00 0 63 0 0
#> 7 24.00 0 37 1 0
#> 11.1 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 72.1 24.00 0 40 0 1
#> 1 24.00 0 23 1 0
#> 84 24.00 0 39 0 1
#> 95 24.00 0 68 0 1
#> 156 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 3.1 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 74 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 172.1 24.00 0 41 0 0
#> 156.1 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 17.1 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 196.2 24.00 0 19 0 0
#> 80.1 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 152.1 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 94.2 24.00 0 51 0 1
#> 48 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 172.2 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 144.1 24.00 0 28 0 1
#> 71.2 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 178.1 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 94.3 24.00 0 51 0 1
#> 200.1 24.00 0 64 0 0
#> 44 24.00 0 56 0 0
#> 121.1 24.00 0 57 1 0
#> 103.1 24.00 0 56 1 0
#> 151.1 24.00 0 42 0 0
#> 38 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 152.2 24.00 0 36 0 1
#> 33.1 24.00 0 53 0 0
#> 148.1 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.436 NA NA NA
#> 2 age, Cure model 0.0118 NA NA NA
#> 3 grade_ii, Cure model 0.0200 NA NA NA
#> 4 grade_iii, Cure model 0.360 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000298 NA NA NA
#> 2 grade_ii, Survival model 0.931 NA NA NA
#> 3 grade_iii, Survival model 0.696 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.43552 0.01185 0.02002 0.35963
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 261 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.43552394 0.01184936 0.02002185 0.35963117
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0002975361 0.9314982360 0.6958925926
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.60063444 0.37174448 0.90769007 0.70846200 0.53043775 0.17191447
#> [7] 0.53043775 0.44476370 0.46447678 0.96338061 0.32445495 0.79094330
#> [13] 0.84839018 0.88443183 0.25157545 0.17191447 0.86060949 0.73710564
#> [19] 0.13730349 0.15459425 0.87853106 0.80407208 0.86060949 0.65590590
#> [25] 0.46447678 0.44476370 0.36073400 0.98444684 0.46447678 0.02594831
#> [31] 0.65590590 0.63296577 0.96338061 0.65590590 0.54874036 0.20491509
#> [37] 0.51132255 0.97919115 0.56668824 0.91926708 0.22082613 0.77781691
#> [43] 0.75107231 0.33704524 0.98967558 0.22082613 0.94158683 0.80407208
#> [49] 0.91926708 0.58381580 0.83585612 0.09995977 0.94716736 0.38275923
#> [55] 0.89027422 0.96338061 0.89027422 0.60063444 0.34919280 0.70109151
#> [61] 0.28237729 0.12003748 0.61700971 0.07134142 0.87257013 0.46447678
#> [67] 0.46447678 0.73002426 0.94716736 0.29739722 0.67886454 0.76469360
#> [73] 0.84839018 0.76469360 0.72294410 0.31136553 0.38275923 0.40332363
#> [79] 0.80407208 0.63296577 0.57534780 0.58381580 0.89027422 0.91926708
#> [85] 0.74412120 0.94716736 0.55782316 0.25157545 0.52087931 0.79094330
#> [91] 0.02594831 0.82322736 0.75792847 0.91926708 0.41374417 0.61700971
#> [97] 0.67886454 0.67886454 0.91349645 0.98967558 0.82322736 0.77781691
#> [103] 0.41374417 0.43433755 0.71575854 0.84212301 0.63296577 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 110 68 52 130 108 169 108.1 170 58 149 99 180 140
#> 17.56 20.62 10.42 16.47 18.29 22.41 18.29 19.54 19.34 8.37 21.19 14.82 12.68
#> 107 175 169.1 154 26 113 15 49 57 154.1 30 55 170.1
#> 11.18 21.91 22.41 12.63 15.77 22.86 22.68 12.19 14.46 12.63 17.43 19.34 19.54
#> 190 77 58.1 24 30.1 111 149.1 30.2 51 194 97 70 40
#> 20.81 7.27 19.34 23.89 17.43 17.45 8.37 17.43 18.23 22.40 19.14 7.38 18.00
#> 61 66 157 167 90 127 66.1 145 57.1 61.1 184 123 129
#> 10.12 22.13 15.10 15.55 20.94 3.53 22.13 10.07 14.46 10.12 17.77 13.00 23.41
#> 187 128 10 149.2 10.1 110.1 32 106 136 92 117 78 42
#> 9.92 20.35 10.53 8.37 10.53 17.56 20.90 16.67 21.83 22.92 17.46 23.88 12.43
#> 58.2 58.3 100 187.1 139 45 18 140.1 18.1 79 153 128.1 150
#> 19.34 19.34 16.07 9.92 21.49 17.42 15.21 12.68 15.21 16.23 21.33 20.35 20.33
#> 57.2 111.1 134 184.1 10.2 61.2 39 187.2 41 175.1 8 180.1 24.1
#> 14.46 17.45 17.81 17.77 10.53 10.12 15.59 9.92 18.02 21.91 18.43 14.82 23.89
#> 13 29 61.3 166 117.1 45.1 45.2 93 127.1 13.1 157.1 166.1 105
#> 14.34 15.45 10.12 19.98 17.46 17.42 17.42 10.33 3.53 14.34 15.10 19.98 19.75
#> 192 14 111.2 126 116 31 72 20 87 200 141 11 174
#> 16.44 12.89 17.45 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 165 151 152 75 21 94 161 148 116.1 71 196 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 71.1 196.1 47 87.1 3 75.1 94.1 198 12 7 11.1 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 1 84 95 156 160 103 3.1 33 131 34 74 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 156.1 53 17 22 17.1 138 144 196.2 80.1 98 152.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 94.2 48 198.1 172.2 2 144.1 71.2 185 104 178.1 122 94.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 44 121.1 103.1 151.1 38 95.1 152.2 33.1 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[100]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01100183 0.77271437 0.43380449
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.326919994 0.005647409 0.146440469
#> grade_iii, Cure model
#> 0.550513990
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x560dde43d5a8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 97 19.14 1 65 0 1
#> 128 20.35 1 35 0 1
#> 99 21.19 1 38 0 1
#> 52 10.42 1 52 0 1
#> 8 18.43 1 32 0 0
#> 195 11.76 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 66 22.13 1 53 0 0
#> 26 15.77 1 49 0 1
#> 149 8.37 1 33 1 0
#> 91 5.33 1 61 0 1
#> 164 23.60 1 76 0 1
#> 145 10.07 1 65 1 0
#> 10 10.53 1 34 0 0
#> 96 14.54 1 33 0 1
#> 5 16.43 1 51 0 1
#> 60 13.15 1 38 1 0
#> 199 19.81 1 NA 0 1
#> 60.1 13.15 1 38 1 0
#> 37 12.52 1 57 1 0
#> 101 9.97 1 10 0 1
#> 63 22.77 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 199.1 19.81 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 49 12.19 1 48 1 0
#> 168 23.72 1 70 0 0
#> 78 23.88 1 43 0 0
#> 52.1 10.42 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 179 18.63 1 42 0 0
#> 32 20.90 1 37 1 0
#> 175 21.91 1 43 0 0
#> 42 12.43 1 49 0 1
#> 168.1 23.72 1 70 0 0
#> 23 16.92 1 61 0 0
#> 97.1 19.14 1 65 0 1
#> 59 10.16 1 NA 1 0
#> 97.2 19.14 1 65 0 1
#> 29 15.45 1 68 1 0
#> 189 10.51 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 78.1 23.88 1 43 0 0
#> 23.1 16.92 1 61 0 0
#> 168.2 23.72 1 70 0 0
#> 29.1 15.45 1 68 1 0
#> 139 21.49 1 63 1 0
#> 187.1 9.92 1 39 1 0
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 15.1 22.68 1 48 0 0
#> 90 20.94 1 50 0 1
#> 41 18.02 1 40 1 0
#> 86 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 23.2 16.92 1 61 0 0
#> 29.2 15.45 1 68 1 0
#> 4.1 17.64 1 NA 0 1
#> 32.1 20.90 1 37 1 0
#> 114 13.68 1 NA 0 0
#> 181 16.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 192 16.44 1 31 1 0
#> 18 15.21 1 49 1 0
#> 81.1 14.06 1 34 0 0
#> 18.1 15.21 1 49 1 0
#> 111 17.45 1 47 0 1
#> 49.1 12.19 1 48 1 0
#> 41.1 18.02 1 40 1 0
#> 49.2 12.19 1 48 1 0
#> 169 22.41 1 46 0 0
#> 4.2 17.64 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 140 12.68 1 59 1 0
#> 108.1 18.29 1 39 0 1
#> 133.1 14.65 1 57 0 0
#> 155.1 13.08 1 26 0 0
#> 43.1 12.10 1 61 0 1
#> 96.1 14.54 1 33 0 1
#> 58 19.34 1 39 0 0
#> 10.1 10.53 1 34 0 0
#> 180 14.82 1 37 0 0
#> 40 18.00 1 28 1 0
#> 89 11.44 1 NA 0 0
#> 140.1 12.68 1 59 1 0
#> 139.1 21.49 1 63 1 0
#> 79 16.23 1 54 1 0
#> 89.1 11.44 1 NA 0 0
#> 99.1 21.19 1 38 0 1
#> 106 16.67 1 49 1 0
#> 56 12.21 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 68.1 20.62 1 44 0 0
#> 133.2 14.65 1 57 0 0
#> 179.1 18.63 1 42 0 0
#> 134 17.81 1 47 1 0
#> 29.3 15.45 1 68 1 0
#> 110 17.56 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 76 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 68.2 20.62 1 44 0 0
#> 133.3 14.65 1 57 0 0
#> 15.2 22.68 1 48 0 0
#> 194 22.40 1 38 0 1
#> 153 21.33 1 55 1 0
#> 147 24.00 0 76 1 0
#> 137 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 65 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 48 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 2 24.00 0 9 0 0
#> 121 24.00 0 57 1 0
#> 33.2 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 178 24.00 0 52 1 0
#> 163.1 24.00 0 66 0 0
#> 135.1 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 172.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 119.1 24.00 0 17 0 0
#> 147.1 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 112 24.00 0 61 0 0
#> 54 24.00 0 53 1 0
#> 84 24.00 0 39 0 1
#> 83 24.00 0 6 0 0
#> 173 24.00 0 19 0 1
#> 95 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 172.2 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 141 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 82 24.00 0 34 0 0
#> 31 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 84.1 24.00 0 39 0 1
#> 20.1 24.00 0 46 1 0
#> 98 24.00 0 34 1 0
#> 126 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 28 24.00 0 67 1 0
#> 156 24.00 0 50 1 0
#> 22.1 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 193.1 24.00 0 45 0 1
#> 120 24.00 0 68 0 1
#> 33.3 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 33.4 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 182.1 24.00 0 35 0 0
#> 112.2 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 47 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 200 24.00 0 64 0 0
#> 75.1 24.00 0 21 1 0
#> 9 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 160 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 120.1 24.00 0 68 0 1
#> 200.2 24.00 0 64 0 0
#> 1 24.00 0 23 1 0
#> 71.1 24.00 0 51 0 0
#> 65.2 24.00 0 57 1 0
#> 146 24.00 0 63 1 0
#> 141.2 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 193.2 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.327 NA NA NA
#> 2 age, Cure model 0.00565 NA NA NA
#> 3 grade_ii, Cure model 0.146 NA NA NA
#> 4 grade_iii, Cure model 0.551 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0110 NA NA NA
#> 2 grade_ii, Survival model 0.773 NA NA NA
#> 3 grade_iii, Survival model 0.434 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.326920 0.005647 0.146440 0.550514
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 255.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.326919994 0.005647409 0.146440469 0.550513990
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01100183 0.77271437 0.43380449
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.245484869 0.215442627 0.139691423 0.902359618 0.296383003 0.047635807
#> [7] 0.696381768 0.858901406 0.978539765 0.090244204 0.505501417 0.967756174
#> [13] 0.989257589 0.031314814 0.924240735 0.880546838 0.674697770 0.473755752
#> [19] 0.718278577 0.718278577 0.783362732 0.935239061 0.039919659 0.946188159
#> [25] 0.826808482 0.013125885 0.001623438 0.902359618 0.783362732 0.275451438
#> [31] 0.168711400 0.100146405 0.804962139 0.013125885 0.410447159 0.245484869
#> [37] 0.245484869 0.558771278 0.307155378 0.001623438 0.410447159 0.013125885
#> [43] 0.558771278 0.110432493 0.946188159 0.537548029 0.187051424 0.047635807
#> [49] 0.158789027 0.328315987 0.008080663 0.494861575 0.410447159 0.558771278
#> [55] 0.168711400 0.452530033 0.516163694 0.631927680 0.463208511 0.600336035
#> [61] 0.696381768 0.600336035 0.379729693 0.826808482 0.328315987 0.826808482
#> [67] 0.071340350 0.739894949 0.761669615 0.307155378 0.631927680 0.739894949
#> [73] 0.858901406 0.674697770 0.225332826 0.880546838 0.621296863 0.348952323
#> [79] 0.761669615 0.110432493 0.484331141 0.139691423 0.441866523 0.815849977
#> [85] 0.379729693 0.526818004 0.187051424 0.631927680 0.275451438 0.359245006
#> [91] 0.558771278 0.369452529 0.537548029 0.235376878 0.400093000 0.187051424
#> [97] 0.631927680 0.047635807 0.080800401 0.129771762 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 97 128 99 52 8 15 81 43 70 66 26 149 91
#> 19.14 20.35 21.19 10.42 18.43 22.68 14.06 12.10 7.38 22.13 15.77 8.37 5.33
#> 164 145 10 96 5 60 60.1 37 101 63 187 49 168
#> 23.60 10.07 10.53 14.54 16.43 13.15 13.15 12.52 9.97 22.77 9.92 12.19 23.72
#> 78 52.1 37.1 179 32 175 42 168.1 23 97.1 97.2 29 108
#> 23.88 10.42 12.52 18.63 20.90 21.91 12.43 23.72 16.92 19.14 19.14 15.45 18.29
#> 78.1 23.1 168.2 29.1 139 187.1 39 68 15.1 90 41 86 100
#> 23.88 16.92 23.72 15.45 21.49 9.92 15.59 20.62 22.68 20.94 18.02 23.81 16.07
#> 23.2 29.2 32.1 181 125 133 192 18 81.1 18.1 111 49.1 41.1
#> 16.92 15.45 20.90 16.46 15.65 14.65 16.44 15.21 14.06 15.21 17.45 12.19 18.02
#> 49.2 169 155 140 108.1 133.1 155.1 43.1 96.1 58 10.1 180 40
#> 12.19 22.41 13.08 12.68 18.29 14.65 13.08 12.10 14.54 19.34 10.53 14.82 18.00
#> 140.1 139.1 79 99.1 106 56 111.1 6 68.1 133.2 179.1 134 29.3
#> 12.68 21.49 16.23 21.19 16.67 12.21 17.45 15.64 20.62 14.65 18.63 17.81 15.45
#> 110 39.1 76 45 68.2 133.3 15.2 194 153 147 137 33 33.1
#> 17.56 15.59 19.22 17.42 20.62 14.65 22.68 22.40 21.33 24.00 24.00 24.00 24.00
#> 163 75 19 65 119 48 191 2 121 33.2 172 12 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 178 163.1 135.1 176 172.1 17 119.1 147.1 102 112 54 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 173 95 152 172.2 20 141 141.1 112.1 82 31 46 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 22 84.1 20.1 98 126 182 193 116 28 156 22.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 120 33.3 44 33.4 165 182.1 112.2 161 47 151 200 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 200.1 160 65.1 122 132 38 98.1 120.1 200.2 1 71.1 65.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 141.2 173.1 193.2 35
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 2
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>
#> $cure_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 0
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>